Search Results for author: Hongming Zhang

Found 91 papers, 58 papers with code

Beyond Relevance: Evaluate and Improve Retrievers on Perspective Awareness

1 code implementation4 May 2024 Xinran Zhao, Tong Chen, Sihao Chen, Hongming Zhang, Tongshuang Wu

In this work, we study whether retrievers can recognize and respond to different perspectives of the queries -- beyond finding relevant documents for a claim, can retrievers distinguish supporting vs. opposing documents?

Information Retrieval Retrieval

NegotiationToM: A Benchmark for Stress-testing Machine Theory of Mind on Negotiation Surrounding

no code implementations21 Apr 2024 Chunkit Chan, Cheng Jiayang, Yauwai Yim, Zheye Deng, Wei Fan, Haoran Li, Xin Liu, Hongming Zhang, Weiqi Wang, Yangqiu Song

Large Language Models (LLMs) have sparked substantial interest and debate concerning their potential emergence of Theory of Mind (ToM) ability.

Conceptual and Unbiased Reasoning in Language Models

no code implementations30 Mar 2024 Ben Zhou, Hongming Zhang, Sihao Chen, Dian Yu, Hongwei Wang, Baolin Peng, Dan Roth, Dong Yu

Conceptual reasoning, the ability to reason in abstract and high-level perspectives, is key to generalization in human cognition.

Decision Making

WebVoyager: Building an End-to-End Web Agent with Large Multimodal Models

1 code implementation25 Jan 2024 Hongliang He, Wenlin Yao, Kaixin Ma, Wenhao Yu, Yong Dai, Hongming Zhang, Zhenzhong Lan, Dong Yu

The rapid advancement of large language models (LLMs) has led to a new era marked by the development of autonomous applications in real-world scenarios, which drives innovation in creating advanced web agents.

Dense X Retrieval: What Retrieval Granularity Should We Use?

1 code implementation11 Dec 2023 Tong Chen, Hongwei Wang, Sihao Chen, Wenhao Yu, Kaixin Ma, Xinran Zhao, Hongming Zhang, Dong Yu

We discover that the retrieval unit choice significantly impacts the performance of both retrieval and downstream tasks.

Retrieval Sentence +1

Efficient Reinforcement Learning from Partial Observability

no code implementations20 Nov 2023 Hongming Zhang, Tongzheng Ren, Chenjun Xiao, Dale Schuurmans, Bo Dai

In most real-world reinforcement learning applications, state information is only partially observable, which breaks the Markov decision process assumption and leads to inferior performance for algorithms that conflate observations with state.

Partially Observable Reinforcement Learning reinforcement-learning

Chain-of-Note: Enhancing Robustness in Retrieval-Augmented Language Models

no code implementations15 Nov 2023 Wenhao Yu, Hongming Zhang, Xiaoman Pan, Kaixin Ma, Hongwei Wang, Dong Yu

In response to these challenges, we introduces Chain-of-Noting (CoN), a novel approach aimed at improving the robustness of RALMs in facing noisy, irrelevant documents and in handling unknown scenarios.

Hallucination Retrieval

AbsPyramid: Benchmarking the Abstraction Ability of Language Models with a Unified Entailment Graph

1 code implementation15 Nov 2023 Zhaowei Wang, Haochen Shi, Weiqi Wang, Tianqing Fang, Hongming Zhang, Sehyun Choi, Xin Liu, Yangqiu Song

Cognitive research indicates that abstraction ability is essential in human intelligence, which remains under-explored in language models.

Benchmarking

A Closer Look at the Self-Verification Abilities of Large Language Models in Logical Reasoning

1 code implementation14 Nov 2023 Ruixin Hong, Hongming Zhang, Xinyu Pang, Dong Yu, ChangShui Zhang

In this paper, we take a closer look at the self-verification abilities of LLMs in the context of logical reasoning, focusing on their ability to identify logical fallacies accurately.

Logical Fallacies Logical Reasoning

Sub-Sentence Encoder: Contrastive Learning of Propositional Semantic Representations

1 code implementation7 Nov 2023 Sihao Chen, Hongming Zhang, Tong Chen, Ben Zhou, Wenhao Yu, Dian Yu, Baolin Peng, Hongwei Wang, Dan Roth, Dong Yu

We introduce sub-sentence encoder, a contrastively-learned contextual embedding model for fine-grained semantic representation of text.

Contrastive Learning Semantic Similarity +3

On the Dimensionality of Sentence Embeddings

no code implementations23 Oct 2023 Hongwei Wang, Hongming Zhang, Dong Yu

Therefore, we propose a two-step training method for sentence representation learning models, wherein the encoder and the pooler are optimized separately to mitigate the overall performance loss in low-dimension scenarios.

Sentence Sentence Classification +3

SocREval: Large Language Models with the Socratic Method for Reference-Free Reasoning Evaluation

1 code implementation29 Sep 2023 Hangfeng He, Hongming Zhang, Dan Roth

Existing reference-free reasoning evaluation metrics, while eliminating the need for human-crafted reasoning chains as references, often require fine-tuning with human-derived chains before evaluation, complicating the process and questioning their adaptability to other datasets.

LASER: LLM Agent with State-Space Exploration for Web Navigation

1 code implementation15 Sep 2023 Kaixin Ma, Hongming Zhang, Hongwei Wang, Xiaoman Pan, Wenhao Yu, Dong Yu

We evaluate our proposed LLM Agent with State-Space ExploRation (LASER) on both the WebShop task and amazon. com.

Decision Making

A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

no code implementations8 Jul 2023 Neeraj Varshney, Wenlin Yao, Hongming Zhang, Jianshu Chen, Dong Yu

Specifically, the detection technique achieves a recall of ~88% and the mitigation technique successfully mitigates 57. 6% of the correctly detected hallucinations.

Hallucination

PIVOINE: Instruction Tuning for Open-world Information Extraction

1 code implementation24 May 2023 Keming Lu, Xiaoman Pan, Kaiqiang Song, Hongming Zhang, Dong Yu, Jianshu Chen

In particular, we construct INSTRUCTOPENWIKI, a substantial instruction tuning dataset for Open-world IE enriched with a comprehensive corpus, extensive annotations, and diverse instructions.

Instruction Following Language Modelling +1

Getting Sick After Seeing a Doctor? Diagnosing and Mitigating Knowledge Conflicts in Event Temporal Reasoning

no code implementations24 May 2023 Tianqing Fang, Zhaowei Wang, Wenxuan Zhou, Hongming Zhang, Yangqiu Song, Muhao Chen

However, knowledge conflicts arise when there is a mismatch between the actual temporal relations of events in the context and the prior knowledge or biases learned by the model.

counterfactual Data Augmentation +2

Bridging Continuous and Discrete Spaces: Interpretable Sentence Representation Learning via Compositional Operations

1 code implementation24 May 2023 James Y. Huang, Wenlin Yao, Kaiqiang Song, Hongming Zhang, Muhao Chen, Dong Yu

It is unclear whether the compositional semantics of sentences can be directly reflected as compositional operations in the embedding space.

Decoder Semantic Similarity +5

Open-Domain Event Graph Induction for Mitigating Framing Bias

no code implementations22 May 2023 Siyi Liu, Hongming Zhang, Hongwei Wang, Kaiqiang Song, Dan Roth, Dong Yu

However, none of the existing methods have explicitly addressed the issue of framing bias that is inherent in news articles.

CEO: Corpus-based Open-Domain Event Ontology Induction

no code implementations22 May 2023 Nan Xu, Hongming Zhang, Jianshu Chen

Existing event-centric NLP models often only apply to the pre-defined ontology, which significantly restricts their generalization capabilities.

COLA: Contextualized Commonsense Causal Reasoning from the Causal Inference Perspective

1 code implementation9 May 2023 Zhaowei Wang, Quyet V. Do, Hongming Zhang, Jiayao Zhang, Weiqi Wang, Tianqing Fang, Yangqiu Song, Ginny Y. Wong, Simon See

This paper proposes a new task to detect commonsense causation between two events in an event sequence (i. e., context), called contextualized commonsense causal reasoning.

Causal Inference CoLA +1

Faithful Question Answering with Monte-Carlo Planning

1 code implementation4 May 2023 Ruixin Hong, Hongming Zhang, Hong Zhao, Dong Yu, ChangShui Zhang

In this paper, we propose FAME (FAithful question answering with MontE-carlo planning) to answer questions based on faithful reasoning steps.

Decision Making Question Answering +1

Replay Memory as An Empirical MDP: Combining Conservative Estimation with Experience Replay

1 code implementation ICLR 2023 Hongming Zhang, Chenjun Xiao, Han Wang, Jun Jin, Bo Xu, Martin Müller

In this work, we further exploit the information in the replay memory by treating it as an empirical \emph{Replay Memory MDP (RM-MDP)}.

Global Constraints with Prompting for Zero-Shot Event Argument Classification

1 code implementation9 Feb 2023 Zizheng Lin, Hongming Zhang, Yangqiu Song

In this work, we propose to use global constraints with prompting to effectively tackles event argument classification without any annotation and task-specific training.

Event Extraction Language Modelling

Video State-Changing Object Segmentation

1 code implementation ICCV 2023 Jiangwei Yu, Xiang Li, Xinran Zhao, Hongming Zhang, Yu-Xiong Wang

Learning about object state changes in Video Object Segmentation (VOS) is crucial for understanding and interacting with the visual world.

Object Representation Learning +4

Rethinking with Retrieval: Faithful Large Language Model Inference

1 code implementation31 Dec 2022 Hangfeng He, Hongming Zhang, Dan Roth

To address this issue, we propose a novel post-processing approach, rethinking with retrieval (RR), which retrieves relevant external knowledge based on the decomposed reasoning steps obtained from the chain-of-thought (CoT) prompting.

Language Modelling Large Language Model +2

ZeroKBC: A Comprehensive Benchmark for Zero-Shot Knowledge Base Completion

1 code implementation6 Dec 2022 Pei Chen, Wenlin Yao, Hongming Zhang, Xiaoman Pan, Dian Yu, Dong Yu, Jianshu Chen

However, there has been limited research on the zero-shot KBC settings, where we need to deal with unseen entities and relations that emerge in a constantly growing knowledge base.

Knowledge Base Completion Knowledge Graphs

Build generally reusable agent-environment interaction models

no code implementations13 Nov 2022 Jun Jin, Hongming Zhang, Jun Luo

This paper tackles the problem of how to pre-train a model and make it generally reusable backbones for downstream task learning.

Efficient Zero-shot Event Extraction with Context-Definition Alignment

1 code implementation9 Nov 2022 Hongming Zhang, Wenlin Yao, Dong Yu

We argue that using the static embedding of the event type name might not be enough because a single word could be ambiguous, and we need a sentence to define the type semantics accurately.

Contrastive Learning Sentence +1

Investigating Fairness Disparities in Peer Review: A Language Model Enhanced Approach

1 code implementation7 Nov 2022 Jiayao Zhang, Hongming Zhang, Zhun Deng, Dan Roth

We distill several insights from our analysis on study the peer review process with the help of large LMs.

Fairness Language Modelling +1

Knowledge-in-Context: Towards Knowledgeable Semi-Parametric Language Models

no code implementations28 Oct 2022 Xiaoman Pan, Wenlin Yao, Hongming Zhang, Dian Yu, Dong Yu, Jianshu Chen

In this paper, we develop a novel semi-parametric language model architecture, Knowledge-in-Context (KiC), which empowers a parametric text-to-text language model with a knowledge-rich external memory.

Common Sense Reasoning Coreference Resolution +7

Salience Allocation as Guidance for Abstractive Summarization

1 code implementation22 Oct 2022 Fei Wang, Kaiqiang Song, Hongming Zhang, Lifeng Jin, Sangwoo Cho, Wenlin Yao, Xiaoyang Wang, Muhao Chen, Dong Yu

Recent literature adds extractive summaries as guidance for abstractive summarization models to provide hints of salient content and achieves better performance.

Abstractive Text Summarization

Z-LaVI: Zero-Shot Language Solver Fueled by Visual Imagination

1 code implementation21 Oct 2022 Yue Yang, Wenlin Yao, Hongming Zhang, Xiaoyang Wang, Dong Yu, Jianshu Chen

Large-scale pretrained language models have made significant advances in solving downstream language understanding tasks.

Language Modelling Retrieval +2

MICO: A Multi-alternative Contrastive Learning Framework for Commonsense Knowledge Representation

1 code implementation14 Oct 2022 Ying Su, ZiHao Wang, Tianqing Fang, Hongming Zhang, Yangqiu Song, Tong Zhang

Commonsense reasoning tasks such as commonsense knowledge graph completion and commonsense question answering require powerful representation learning.

Contrastive Learning Question Answering +2

Multilingual Word Sense Disambiguation with Unified Sense Representation

1 code implementation COLING 2022 Ying Su, Hongming Zhang, Yangqiu Song, Tong Zhang

As a key natural language processing (NLP) task, word sense disambiguation (WSD) evaluates how well NLP models can understand the lexical semantics of words under specific contexts.

Word Sense Disambiguation

PseudoReasoner: Leveraging Pseudo Labels for Commonsense Knowledge Base Population

1 code implementation14 Oct 2022 Tianqing Fang, Quyet V. Do, Hongming Zhang, Yangqiu Song, Ginny Y. Wong, Simon See

We propose PseudoReasoner, a semi-supervised learning framework for CSKB population that uses a teacher model pre-trained on CSKBs to provide pseudo labels on the unlabeled candidate dataset for a student model to learn from.

Domain Generalization Knowledge Base Population

SubeventWriter: Iterative Sub-event Sequence Generation with Coherence Controller

1 code implementation13 Oct 2022 Zhaowei Wang, Hongming Zhang, Tianqing Fang, Yangqiu Song, Ginny Y. Wong, Simon See

In this paper, we propose a new task of sub-event generation for an unseen process to evaluate the understanding of the coherence of sub-event actions and objects.

CIKQA: Learning Commonsense Inference with a Unified Knowledge-in-the-loop QA Paradigm

no code implementations12 Oct 2022 Hongming Zhang, Yintong Huo, Yanai Elazar, Yangqiu Song, Yoav Goldberg, Dan Roth

We first align commonsense tasks with relevant knowledge from commonsense knowledge bases and ask humans to annotate whether the knowledge is enough or not.

Question Answering Task 2

Are All Steps Equally Important? Benchmarking Essentiality Detection of Events

no code implementations8 Oct 2022 Haoyu Wang, Hongming Zhang, Yueguan Wang, Yuqian Deng, Muhao Chen, Dan Roth

In this paper, we address this gap by examining the extent to which current models comprehend the essentiality of step events in relation to a goal event.

Benchmarking

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

3 code implementations9 Jun 2022 Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, Abu Awal Md Shoeb, Abubakar Abid, Adam Fisch, Adam R. Brown, Adam Santoro, Aditya Gupta, Adrià Garriga-Alonso, Agnieszka Kluska, Aitor Lewkowycz, Akshat Agarwal, Alethea Power, Alex Ray, Alex Warstadt, Alexander W. Kocurek, Ali Safaya, Ali Tazarv, Alice Xiang, Alicia Parrish, Allen Nie, Aman Hussain, Amanda Askell, Amanda Dsouza, Ambrose Slone, Ameet Rahane, Anantharaman S. Iyer, Anders Andreassen, Andrea Madotto, Andrea Santilli, Andreas Stuhlmüller, Andrew Dai, Andrew La, Andrew Lampinen, Andy Zou, Angela Jiang, Angelica Chen, Anh Vuong, Animesh Gupta, Anna Gottardi, Antonio Norelli, Anu Venkatesh, Arash Gholamidavoodi, Arfa Tabassum, Arul Menezes, Arun Kirubarajan, Asher Mullokandov, Ashish Sabharwal, Austin Herrick, Avia Efrat, Aykut Erdem, Ayla Karakaş, B. Ryan Roberts, Bao Sheng Loe, Barret Zoph, Bartłomiej Bojanowski, Batuhan Özyurt, Behnam Hedayatnia, Behnam Neyshabur, Benjamin Inden, Benno Stein, Berk Ekmekci, Bill Yuchen Lin, Blake Howald, Bryan Orinion, Cameron Diao, Cameron Dour, Catherine Stinson, Cedrick Argueta, César Ferri Ramírez, Chandan Singh, Charles Rathkopf, Chenlin Meng, Chitta Baral, Chiyu Wu, Chris Callison-Burch, Chris Waites, Christian Voigt, Christopher D. Manning, Christopher Potts, Cindy Ramirez, Clara E. Rivera, Clemencia Siro, Colin Raffel, Courtney Ashcraft, Cristina Garbacea, Damien Sileo, Dan Garrette, Dan Hendrycks, Dan Kilman, Dan Roth, Daniel Freeman, Daniel Khashabi, Daniel Levy, Daniel Moseguí González, Danielle Perszyk, Danny Hernandez, Danqi Chen, Daphne Ippolito, Dar Gilboa, David Dohan, David Drakard, David Jurgens, Debajyoti Datta, Deep Ganguli, Denis Emelin, Denis Kleyko, Deniz Yuret, Derek Chen, Derek Tam, Dieuwke Hupkes, Diganta Misra, Dilyar Buzan, Dimitri Coelho Mollo, Diyi Yang, Dong-Ho Lee, Dylan Schrader, Ekaterina Shutova, Ekin Dogus Cubuk, Elad Segal, Eleanor Hagerman, Elizabeth Barnes, Elizabeth Donoway, Ellie Pavlick, Emanuele Rodola, Emma Lam, Eric Chu, Eric Tang, Erkut Erdem, Ernie Chang, Ethan A. Chi, Ethan Dyer, Ethan Jerzak, Ethan Kim, Eunice Engefu Manyasi, Evgenii Zheltonozhskii, Fanyue Xia, Fatemeh Siar, Fernando Martínez-Plumed, Francesca Happé, Francois Chollet, Frieda Rong, Gaurav Mishra, Genta Indra Winata, Gerard de Melo, Germán Kruszewski, Giambattista Parascandolo, Giorgio Mariani, Gloria Wang, Gonzalo Jaimovitch-López, Gregor Betz, Guy Gur-Ari, Hana Galijasevic, Hannah Kim, Hannah Rashkin, Hannaneh Hajishirzi, Harsh Mehta, Hayden Bogar, Henry Shevlin, Hinrich Schütze, Hiromu Yakura, Hongming Zhang, Hugh Mee Wong, Ian Ng, Isaac Noble, Jaap Jumelet, Jack Geissinger, Jackson Kernion, Jacob Hilton, Jaehoon Lee, Jaime Fernández Fisac, James B. Simon, James Koppel, James Zheng, James Zou, Jan Kocoń, Jana Thompson, Janelle Wingfield, Jared Kaplan, Jarema Radom, Jascha Sohl-Dickstein, Jason Phang, Jason Wei, Jason Yosinski, Jekaterina Novikova, Jelle Bosscher, Jennifer Marsh, Jeremy Kim, Jeroen Taal, Jesse Engel, Jesujoba Alabi, Jiacheng Xu, Jiaming Song, Jillian Tang, Joan Waweru, John Burden, John Miller, John U. Balis, Jonathan Batchelder, Jonathan Berant, Jörg Frohberg, Jos Rozen, Jose Hernandez-Orallo, Joseph Boudeman, Joseph Guerr, Joseph Jones, Joshua B. Tenenbaum, Joshua S. Rule, Joyce Chua, Kamil Kanclerz, Karen Livescu, Karl Krauth, Karthik Gopalakrishnan, Katerina Ignatyeva, Katja Markert, Kaustubh D. Dhole, Kevin Gimpel, Kevin Omondi, Kory Mathewson, Kristen Chiafullo, Ksenia Shkaruta, Kumar Shridhar, Kyle McDonell, Kyle Richardson, Laria Reynolds, Leo Gao, Li Zhang, Liam Dugan, Lianhui Qin, Lidia Contreras-Ochando, Louis-Philippe Morency, Luca Moschella, Lucas Lam, Lucy Noble, Ludwig Schmidt, Luheng He, Luis Oliveros Colón, Luke Metz, Lütfi Kerem Şenel, Maarten Bosma, Maarten Sap, Maartje ter Hoeve, Maheen Farooqi, Manaal Faruqui, Mantas Mazeika, Marco Baturan, Marco Marelli, Marco Maru, Maria Jose Ramírez Quintana, Marie Tolkiehn, Mario Giulianelli, Martha Lewis, Martin Potthast, Matthew L. Leavitt, Matthias Hagen, Mátyás Schubert, Medina Orduna Baitemirova, Melody Arnaud, Melvin McElrath, Michael A. Yee, Michael Cohen, Michael Gu, Michael Ivanitskiy, Michael Starritt, Michael Strube, Michał Swędrowski, Michele Bevilacqua, Michihiro Yasunaga, Mihir Kale, Mike Cain, Mimee Xu, Mirac Suzgun, Mitch Walker, Mo Tiwari, Mohit Bansal, Moin Aminnaseri, Mor Geva, Mozhdeh Gheini, Mukund Varma T, Nanyun Peng, Nathan A. Chi, Nayeon Lee, Neta Gur-Ari Krakover, Nicholas Cameron, Nicholas Roberts, Nick Doiron, Nicole Martinez, Nikita Nangia, Niklas Deckers, Niklas Muennighoff, Nitish Shirish Keskar, Niveditha S. Iyer, Noah Constant, Noah Fiedel, Nuan Wen, Oliver Zhang, Omar Agha, Omar Elbaghdadi, Omer Levy, Owain Evans, Pablo Antonio Moreno Casares, Parth Doshi, Pascale Fung, Paul Pu Liang, Paul Vicol, Pegah Alipoormolabashi, Peiyuan Liao, Percy Liang, Peter Chang, Peter Eckersley, Phu Mon Htut, Pinyu Hwang, Piotr Miłkowski, Piyush Patil, Pouya Pezeshkpour, Priti Oli, Qiaozhu Mei, Qing Lyu, Qinlang Chen, Rabin Banjade, Rachel Etta Rudolph, Raefer Gabriel, Rahel Habacker, Ramon Risco, Raphaël Millière, Rhythm Garg, Richard Barnes, Rif A. Saurous, Riku Arakawa, Robbe Raymaekers, Robert Frank, Rohan Sikand, Roman Novak, Roman Sitelew, Ronan LeBras, Rosanne Liu, Rowan Jacobs, Rui Zhang, Ruslan Salakhutdinov, Ryan Chi, Ryan Lee, Ryan Stovall, Ryan Teehan, Rylan Yang, Sahib Singh, Saif M. Mohammad, Sajant Anand, Sam Dillavou, Sam Shleifer, Sam Wiseman, Samuel Gruetter, Samuel R. Bowman, Samuel S. Schoenholz, Sanghyun Han, Sanjeev Kwatra, Sarah A. Rous, Sarik Ghazarian, Sayan Ghosh, Sean Casey, Sebastian Bischoff, Sebastian Gehrmann, Sebastian Schuster, Sepideh Sadeghi, Shadi Hamdan, Sharon Zhou, Shashank Srivastava, Sherry Shi, Shikhar Singh, Shima Asaadi, Shixiang Shane Gu, Shubh Pachchigar, Shubham Toshniwal, Shyam Upadhyay, Shyamolima, Debnath, Siamak Shakeri, Simon Thormeyer, Simone Melzi, Siva Reddy, Sneha Priscilla Makini, Soo-Hwan Lee, Spencer Torene, Sriharsha Hatwar, Stanislas Dehaene, Stefan Divic, Stefano Ermon, Stella Biderman, Stephanie Lin, Stephen Prasad, Steven T. Piantadosi, Stuart M. Shieber, Summer Misherghi, Svetlana Kiritchenko, Swaroop Mishra, Tal Linzen, Tal Schuster, Tao Li, Tao Yu, Tariq Ali, Tatsu Hashimoto, Te-Lin Wu, Théo Desbordes, Theodore Rothschild, Thomas Phan, Tianle Wang, Tiberius Nkinyili, Timo Schick, Timofei Kornev, Titus Tunduny, Tobias Gerstenberg, Trenton Chang, Trishala Neeraj, Tushar Khot, Tyler Shultz, Uri Shaham, Vedant Misra, Vera Demberg, Victoria Nyamai, Vikas Raunak, Vinay Ramasesh, Vinay Uday Prabhu, Vishakh Padmakumar, Vivek Srikumar, William Fedus, William Saunders, William Zhang, Wout Vossen, Xiang Ren, Xiaoyu Tong, Xinran Zhao, Xinyi Wu, Xudong Shen, Yadollah Yaghoobzadeh, Yair Lakretz, Yangqiu Song, Yasaman Bahri, Yejin Choi, Yichi Yang, Yiding Hao, Yifu Chen, Yonatan Belinkov, Yu Hou, Yufang Hou, Yuntao Bai, Zachary Seid, Zhuoye Zhao, Zijian Wang, Zijie J. Wang, ZiRui Wang, Ziyi Wu

BIG-bench focuses on tasks that are believed to be beyond the capabilities of current language models.

Common Sense Reasoning Math +1

VD-PCR: Improving Visual Dialog with Pronoun Coreference Resolution

1 code implementation29 May 2022 Xintong Yu, Hongming Zhang, Ruixin Hong, Yangqiu Song, ChangShui Zhang

In this paper, we propose VD-PCR, a novel framework to improve Visual Dialog understanding with Pronoun Coreference Resolution in both implicit and explicit ways.

coreference-resolution Visual Dialog

Query2Particles: Knowledge Graph Reasoning with Particle Embeddings

1 code implementation Findings (NAACL) 2022 Jiaxin Bai, ZiHao Wang, Hongming Zhang, Yangqiu Song

The query embedding method is proposed to answer these queries by jointly encoding queries and entities to the same embedding space.

Complex Query Answering Entity Embeddings

ROCK: Causal Inference Principles for Reasoning about Commonsense Causality

1 code implementation31 Jan 2022 Jiayao Zhang, Hongming Zhang, Weijie J. Su, Dan Roth

Commonsense causality reasoning (CCR) aims at identifying plausible causes and effects in natural language descriptions that are deemed reasonable by an average person.

Causal Inference

A Simple Unified Framework for Anomaly Detection in Deep Reinforcement Learning

no code implementations21 Sep 2021 Hongming Zhang, Ke Sun, Bo Xu, Linglong Kong, Martin Müller

In this paper, we propose a simple yet effective anomaly detection framework for deep RL algorithms that simultaneously considers random, adversarial and out-of-distribution~(OOD) state outliers.

Anomaly Detection Atari Games +3

Learning Constraints and Descriptive Segmentation for Subevent Detection

no code implementations EMNLP 2021 Haoyu Wang, Hongming Zhang, Muhao Chen, Dan Roth

The task of subevent detection aims to resolve this granularity issue, recognizing the membership of multi-granular events in event complexes.

Descriptive Text Segmentation

Zero-shot Event Extraction via Transfer Learning: Challenges and Insights

no code implementations ACL 2021 Qing Lyu, Hongming Zhang, Elior Sulem, Dan Roth

Event extraction has long been a challenging task, addressed mostly with supervised methods that require expensive annotation and are not extensible to new event ontologies.

Natural Language Inference Question Answering +2

Event-Centric Natural Language Processing

no code implementations ACL 2021 Muhao Chen, Hongming Zhang, Qiang Ning, Manling Li, Heng Ji, Kathleen McKeown, Dan Roth

This tutorial targets researchers and practitioners who are interested in AI technologies that help machines understand natural language text, particularly real-world events described in the text.

ASER: Towards Large-scale Commonsense Knowledge Acquisition via Higher-order Selectional Preference over Eventualities

1 code implementation5 Apr 2021 Hongming Zhang, Xin Liu, Haojie Pan, Haowen Ke, Jiefu Ou, Tianqing Fang, Yangqiu Song

After conceptualization with Probase, a selectional preference based concept-instance relational knowledge base, our concept graph contains 15 million conceptualized eventualities and 224 million edges between them.

Discourse Parsing

Joint Coreference Resolution and Character Linking for Multiparty Conversation

1 code implementation EACL 2021 Jiaxin Bai, Hongming Zhang, Yangqiu Song, Kun Xu

Character linking, the task of linking mentioned people in conversations to the real world, is crucial for understanding the conversations.

coreference-resolution Entity Linking

DISCOS: Bridging the Gap between Discourse Knowledge and Commonsense Knowledge

1 code implementation1 Jan 2021 Tianqing Fang, Hongming Zhang, Weiqi Wang, Yangqiu Song, Bin He

On the other hand, generation models have the potential to automatically generate more knowledge.

Text Generation

Unsupervised Label-aware Event Trigger and Argument Classification

no code implementations30 Dec 2020 Hongming Zhang, Haoyu Wang, Dan Roth

Rather than relying on annotated data, our model matches the semantics of identified events with those of event type labels.

Classification Event Extraction +1

Learning Contextual Causality from Time-consecutive Images

1 code implementation13 Dec 2020 Hongming Zhang, Yintong Huo, Xinran Zhao, Yangqiu Song, Dan Roth

Compared with pure text-based approaches, learning causality from the visual signal has the following advantages: (1) Causality knowledge belongs to the commonsense knowledge, which is rarely expressed in the text but rich in videos; (2) Most events in the video are naturally time-ordered, which provides a rich resource for us to mine causality knowledge from; (3) All the objects in the video can be used as context to study the contextual property of causal relations.

What Are You Trying to Do? Semantic Typing of Event Processes

no code implementations CONLL 2020 Muhao Chen, Hongming Zhang, Haoyu Wang, Dan Roth

This paper studies a new cognitively motivated semantic typing task, multi-axis event process typing, that, given anevent process, attempts to infer free-form typelabels describing (i) the type of action made bythe process and (ii) the type of object the pro-cess seeks to affect.

Learning-To-Rank Vocal Bursts Type Prediction

Analogous Process Structure Induction for Sub-event Sequence Prediction

no code implementations EMNLP 2020 Hongming Zhang, Muhao Chen, Haoyu Wang, Yangqiu Song, Dan Roth

Computational and cognitive studies of event understanding suggest that identifying, comprehending, and predicting events depend on having structured representations of a sequence of events and on conceptualizing (abstracting) its components into (soft) event categories.

"What Are You Trying to Do?" Semantic Typing of Event Processes

no code implementations13 Oct 2020 Muhao Chen, Hongming Zhang, Haoyu Wang, Dan Roth

This paper studies a new cognitively motivated semantic typing task, multi-axis event process typing, that, given an event process, attempts to infer free-form type labels describing (i) the type of action made by the process and (ii) the type of object the process seeks to affect.

Learning-To-Rank Object +1

Joint Constrained Learning for Event-Event Relation Extraction

no code implementations EMNLP 2020 Haoyu Wang, Muhao Chen, Hongming Zhang, Dan Roth

Understanding natural language involves recognizing how multiple event mentions structurally and temporally interact with each other.

Event Relation Extraction Relation +1

Efficient Reinforcement Learning Development with RLzoo

1 code implementation18 Sep 2020 Zihan Ding, Tianyang Yu, Yanhua Huang, Hongming Zhang, Guo Li, Quancheng Guo, Luo Mai, Hao Dong

RLzoo provides developers with (i) high-level yet flexible APIs for prototyping DRL agents, and further customising the agents for best performance, (ii) a model zoo where users can import a wide range of DRL agents and easily compare their performance, and (iii) an algorithm that can automatically construct DRL agents with custom components (which are critical to improve agent's performance in custom applications).

reinforcement-learning Reinforcement Learning (RL)

Enriching Large-Scale Eventuality Knowledge Graph with Entailment Relations

1 code implementation AKBC 2020 Changlong Yu, Hongming Zhang, Yangqiu Song, Wilfred Ng, Lifeng Shang

Computational and cognitive studies suggest that the abstraction of eventualities (activities, states, and events) is crucial for humans to understand daily eventualities.

EEG

WinoWhy: A Deep Diagnosis of Essential Commonsense Knowledge for Answering Winograd Schema Challenge

1 code implementation ACL 2020 Hongming Zhang, Xinran Zhao, Yangqiu Song

Experimental results prove that even though pre-trained language representation models have achieved promising progress on the original WSC dataset, they are still struggling at WinoWhy.

Winowhy

TransOMCS: From Linguistic Graphs to Commonsense Knowledge

1 code implementation1 May 2020 Hongming Zhang, Daniel Khashabi, Yangqiu Song, Dan Roth

Commonsense knowledge acquisition is a key problem for artificial intelligence.

Multiplex Word Embeddings for Selectional Preference Acquisition

1 code implementation IJCNLP 2019 Hongming Zhang, Jiaxin Bai, Yan Song, Kun Xu, Changlong Yu, Yangqiu Song, Wilfred Ng, Dong Yu

Therefore, in this paper, we propose a multiplex word embedding model, which can be easily extended according to various relations among words.

Word Embeddings Word Similarity

What You See is What You Get: Visual Pronoun Coreference Resolution in Dialogues

1 code implementation IJCNLP 2019 Xintong Yu, Hongming Zhang, Yangqiu Song, Yan Song, Chang-Shui Zhang

To tackle this challenge, in this paper, we formally define the task of visual-aware pronoun coreference resolution (PCR) and introduce VisPro, a large-scale dialogue PCR dataset, to investigate whether and how the visual information can help resolve pronouns in dialogues.

coreference-resolution Natural Language Understanding

Iterative Update and Unified Representation for Multi-Agent Reinforcement Learning

no code implementations16 Aug 2019 Jiancheng Long, Hongming Zhang, Tianyang Yu, Bo Xu

In this method, iterative update can greatly alleviate the nonstationarity of the environment, unified representation can speed up the interaction with environment and avoid the linear growth of memory usage.

Multi-agent Reinforcement Learning reinforcement-learning +1

Knowledge-aware Pronoun Coreference Resolution

1 code implementation ACL 2019 Hongming Zhang, Yan Song, Yangqiu Song, Dong Yu

Resolving pronoun coreference requires knowledge support, especially for particular domains (e. g., medicine).

coreference-resolution Knowledge Graphs

Incorporating Context and External Knowledge for Pronoun Coreference Resolution

1 code implementation NAACL 2019 Hongming Zhang, Yan Song, Yangqiu Song

Linking pronominal expressions to the correct references requires, in many cases, better analysis of the contextual information and external knowledge.

coreference-resolution

SP-10K: A Large-scale Evaluation Set for Selectional Preference Acquisition

1 code implementation ACL 2019 Hongming Zhang, Hantian Ding, Yangqiu Song

Selectional Preference (SP) is a commonly observed language phenomenon and proved to be useful in many natural language processing tasks.

coreference-resolution

A Logarithmic Barrier Method For Proximal Policy Optimization

no code implementations16 Dec 2018 Cheng Zeng, Hongming Zhang

Specifically, a new surrogate objective with interior penalty method is proposed to avoid the defect arose from exterior penalty method.

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