Search Results for author: Xiubo Geng

Found 43 papers, 21 papers with code

Social Norms-Grounded Machine Ethics in Complex Narrative Situation

no code implementations COLING 2022 Tao Shen, Xiubo Geng, Daxin Jiang

Besides a norm-grounding knowledge model, we present a novel norm-supported ethical judgment model in line with neural module networks to alleviate dilemma situations and improve norm-level explainability.

Cultural Vocal Bursts Intensity Prediction Ethics

Thread of Thought Unraveling Chaotic Contexts

no code implementations15 Nov 2023 Yucheng Zhou, Xiubo Geng, Tao Shen, Chongyang Tao, Guodong Long, Jian-Guang Lou, Jianbing Shen

Large Language Models (LLMs) have ushered in a transformative era in the field of natural language processing, excelling in tasks related to text comprehension and generation.

Reading Comprehension

WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct

1 code implementation18 Aug 2023 Haipeng Luo, Qingfeng Sun, Can Xu, Pu Zhao, JianGuang Lou, Chongyang Tao, Xiubo Geng, QIngwei Lin, Shifeng Chen, Dongmei Zhang

Through extensive experiments on two mathematical reasoning benchmarks, namely GSM8k and MATH, we reveal the extraordinary capabilities of our model.

GSM8K Mathematical Reasoning

Investigating the Learning Behaviour of In-context Learning: A Comparison with Supervised Learning

1 code implementation28 Jul 2023 Xindi Wang, YuFei Wang, Can Xu, Xiubo Geng, BoWen Zhang, Chongyang Tao, Frank Rudzicz, Robert E. Mercer, Daxin Jiang

Large language models (LLMs) have shown remarkable capacity for in-context learning (ICL), where learning a new task from just a few training examples is done without being explicitly pre-trained.

WizardCoder: Empowering Code Large Language Models with Evol-Instruct

1 code implementation14 Jun 2023 Ziyang Luo, Can Xu, Pu Zhao, Qingfeng Sun, Xiubo Geng, Wenxiang Hu, Chongyang Tao, Jing Ma, QIngwei Lin, Daxin Jiang

Moreover, our model even outperforms the largest closed LLMs, Anthropic's Claude and Google's Bard, on HumanEval and HumanEval+.

Code Generation

Knowledge Refinement via Interaction Between Search Engines and Large Language Models

1 code implementation12 May 2023 Jiazhan Feng, Chongyang Tao, Xiubo Geng, Tao Shen, Can Xu, Guodong Long, Dongyan Zhao, Daxin Jiang

Information retrieval (IR) plays a crucial role in locating relevant resources from vast amounts of data, and its applications have evolved from traditional knowledge bases to modern search engines (SEs).

Information Retrieval Retrieval

Augmented Large Language Models with Parametric Knowledge Guiding

1 code implementation8 May 2023 Ziyang Luo, Can Xu, Pu Zhao, Xiubo Geng, Chongyang Tao, Jing Ma, QIngwei Lin, Daxin Jiang

We demonstrate that our PKG framework can enhance the performance of "black-box" LLMs on a range of domain knowledge-intensive tasks that require factual (+7. 9%), tabular (+11. 9%), medical (+3. 0%), and multimodal (+8. 1%) knowledge.

Large Language Models are Strong Zero-Shot Retriever

no code implementations27 Apr 2023 Tao Shen, Guodong Long, Xiubo Geng, Chongyang Tao, Tianyi Zhou, Daxin Jiang

In this work, we propose a simple method that applies a large language model (LLM) to large-scale retrieval in zero-shot scenarios.

Language Modelling Large Language Model +1

WizardLM: Empowering Large Language Models to Follow Complex Instructions

5 code implementations24 Apr 2023 Can Xu, Qingfeng Sun, Kai Zheng, Xiubo Geng, Pu Zhao, Jiazhan Feng, Chongyang Tao, Daxin Jiang

In this paper, we show an avenue for creating large amounts of instruction data with varying levels of complexity using LLM instead of humans.

Instruction Following

On the Robustness of ChatGPT: An Adversarial and Out-of-distribution Perspective

1 code implementation22 Feb 2023 Jindong Wang, Xixu Hu, Wenxin Hou, Hao Chen, Runkai Zheng, Yidong Wang, Linyi Yang, Haojun Huang, Wei Ye, Xiubo Geng, Binxin Jiao, Yue Zhang, Xing Xie

In this paper, we conduct a thorough evaluation of the robustness of ChatGPT from the adversarial and out-of-distribution (OOD) perspective.

Adversarial Robustness Chatbot +1

LexLIP: Lexicon-Bottlenecked Language-Image Pre-Training for Large-Scale Image-Text Retrieval

1 code implementation6 Feb 2023 Ziyang Luo, Pu Zhao, Can Xu, Xiubo Geng, Tao Shen, Chongyang Tao, Jing Ma, Qingwen Lin, Daxin Jiang

The conventional dense retrieval paradigm relies on encoding images and texts into dense representations using dual-stream encoders, however, it faces challenges with low retrieval speed in large-scale retrieval scenarios.

Retrieval Text Retrieval

Iterative Proposal Refinement for Weakly-Supervised Video Grounding

no code implementations CVPR 2023 Meng Cao, Fangyun Wei, Can Xu, Xiubo Geng, Long Chen, Can Zhang, Yuexian Zou, Tao Shen, Daxin Jiang

Weakly-Supervised Video Grounding (WSVG) aims to localize events of interest in untrimmed videos with only video-level annotations.

Video Grounding

LexLIP: Lexicon-Bottlenecked Language-Image Pre-Training for Large-Scale Image-Text Sparse Retrieval

1 code implementation ICCV 2023 Ziyang Luo, Pu Zhao, Can Xu, Xiubo Geng, Tao Shen, Chongyang Tao, Jing Ma, QIngwei Lin, Daxin Jiang

To address this issue, we propose a novel sparse retrieval paradigm for ITR that exploits sparse representations in the vocabulary space for images and texts.

Image Classification Retrieval +2

Adam: Dense Retrieval Distillation with Adaptive Dark Examples

no code implementations20 Dec 2022 Chang Liu, Chongyang Tao, Xiubo Geng, Tao Shen, Dongyan Zhao, Can Xu, Binxing Jiao, Daxin Jiang

Different from previous works that only rely on one positive and hard negatives as candidate passages, we create dark examples that all have moderate relevance to the query through mixing-up and masking in discrete space.

Knowledge Distillation Retrieval

Fine-Grained Distillation for Long Document Retrieval

no code implementations20 Dec 2022 Yucheng Zhou, Tao Shen, Xiubo Geng, Chongyang Tao, Guodong Long, Can Xu, Daxin Jiang

Long document retrieval aims to fetch query-relevant documents from a large-scale collection, where knowledge distillation has become de facto to improve a retriever by mimicking a heterogeneous yet powerful cross-encoder.

Knowledge Distillation Retrieval

LexMAE: Lexicon-Bottlenecked Pretraining for Large-Scale Retrieval

1 code implementation31 Aug 2022 Tao Shen, Xiubo Geng, Chongyang Tao, Can Xu, Xiaolong Huang, Binxing Jiao, Linjun Yang, Daxin Jiang

In large-scale retrieval, the lexicon-weighting paradigm, learning weighted sparse representations in vocabulary space, has shown promising results with high quality and low latency.

Language Modelling Passage Retrieval +1

LED: Lexicon-Enlightened Dense Retriever for Large-Scale Retrieval

1 code implementation29 Aug 2022 Kai Zhang, Chongyang Tao, Tao Shen, Can Xu, Xiubo Geng, Binxing Jiao, Daxin Jiang

The alignment is achieved by weakened knowledge distillations to enlighten the retriever via two aspects -- 1) a lexicon-augmented contrastive objective to challenge the dense encoder and 2) a pair-wise rank-consistent regularization to make dense model's behavior incline to the other.

Representation Learning Retrieval

Towards Robust Ranker for Text Retrieval

no code implementations16 Jun 2022 Yucheng Zhou, Tao Shen, Xiubo Geng, Chongyang Tao, Can Xu, Guodong Long, Binxing Jiao, Daxin Jiang

A ranker plays an indispensable role in the de facto 'retrieval & rerank' pipeline, but its training still lags behind -- learning from moderate negatives or/and serving as an auxiliary module for a retriever.

Passage Retrieval Retrieval +1

HeterMPC: A Heterogeneous Graph Neural Network for Response Generation in Multi-Party Conversations

1 code implementation ACL 2022 Jia-Chen Gu, Chao-Hong Tan, Chongyang Tao, Zhen-Hua Ling, Huang Hu, Xiubo Geng, Daxin Jiang

To address these challenges, we present HeterMPC, a heterogeneous graph-based neural network for response generation in MPCs which models the semantics of utterances and interlocutors simultaneously with two types of nodes in a graph.

Response Generation

PCL: Peer-Contrastive Learning with Diverse Augmentations for Unsupervised Sentence Embeddings

1 code implementation28 Jan 2022 Qiyu Wu, Chongyang Tao, Tao Shen, Can Xu, Xiubo Geng, Daxin Jiang

A straightforward solution is resorting to more diverse positives from a multi-augmenting strategy, while an open question remains about how to unsupervisedly learn from the diverse positives but with uneven augmenting qualities in the text field.

Contrastive Learning Open-Ended Question Answering +2

Multimodal Dialogue Response Generation

no code implementations ACL 2022 Qingfeng Sun, Yujing Wang, Can Xu, Kai Zheng, Yaming Yang, Huang Hu, Fei Xu, Jessica Zhang, Xiubo Geng, Daxin Jiang

In such a low-resource setting, we devise a novel conversational agent, Divter, in order to isolate parameters that depend on multimodal dialogues from the entire generation model.

Dialogue Generation Response Generation +1

EventBERT: A Pre-Trained Model for Event Correlation Reasoning

no code implementations13 Oct 2021 Yucheng Zhou, Xiubo Geng, Tao Shen, Guodong Long, Daxin Jiang

Event correlation reasoning infers whether a natural language paragraph containing multiple events conforms to human common sense.

Cloze Test Common Sense Reasoning +1

Building an Efficient and Effective Retrieval-based Dialogue System via Mutual Learning

no code implementations1 Oct 2021 Chongyang Tao, Jiazhan Feng, Chang Liu, Juntao Li, Xiubo Geng, Daxin Jiang

For this task, the adoption of pre-trained language models (such as BERT) has led to remarkable progress in a number of benchmarks.

Re-Ranking Retrieval

Reasoning over Entity-Action-Location Graph for Procedural Text Understanding

no code implementations ACL 2021 Hao Huang, Xiubo Geng, Jian Pei, Guodong Long, Daxin Jiang

Procedural text understanding aims at tracking the states (e. g., create, move, destroy) and locations of the entities mentioned in a given paragraph.

graph construction Procedural Text Understanding +1

MPC-BERT: A Pre-Trained Language Model for Multi-Party Conversation Understanding

1 code implementation ACL 2021 Jia-Chen Gu, Chongyang Tao, Zhen-Hua Ling, Can Xu, Xiubo Geng, Daxin Jiang

Recently, various neural models for multi-party conversation (MPC) have achieved impressive improvements on a variety of tasks such as addressee recognition, speaker identification and response prediction.

Language Modelling Speaker Identification

Improving Zero-Shot Cross-lingual Transfer for Multilingual Question Answering over Knowledge Graph

no code implementations NAACL 2021 Yucheng Zhou, Xiubo Geng, Tao Shen, Wenqiang Zhang, Daxin Jiang

That is, we can only access training data in a high-resource language, while need to answer multilingual questions without any labeled data in target languages.

Bilingual Lexicon Induction Question Answering +1

Maria: A Visual Experience Powered Conversational Agent

1 code implementation ACL 2021 Zujie Liang, Huang Hu, Can Xu, Chongyang Tao, Xiubo Geng, Yining Chen, Fan Liang, Daxin Jiang

The retriever aims to retrieve a correlated image to the dialog from an image index, while the visual concept detector extracts rich visual knowledge from the image.

ChemistryQA: A Complex Question Answering Dataset from Chemistry

no code implementations1 Jan 2021 Zhuoyu Wei, Wei Ji, Xiubo Geng, Yining Chen, Baihua Chen, Tao Qin, Daxin Jiang

We notice that some real-world QA tasks are more complex, which cannot be solved by end-to-end neural networks or translated to any kind of formal representations.

Machine Reading Comprehension Question Answering

Towards Interpretable Reasoning over Paragraph Effects in Situation

1 code implementation EMNLP 2020 Mucheng Ren, Xiubo Geng, Tao Qin, Heyan Huang, Daxin Jiang

We focus on the task of reasoning over paragraph effects in situation, which requires a model to understand the cause and effect described in a background paragraph, and apply the knowledge to a novel situation.

Knowledge-Aware Procedural Text Understanding with Multi-Stage Training

no code implementations28 Sep 2020 Zhihan Zhang, Xiubo Geng, Tao Qin, Yunfang Wu, Daxin Jiang

In this work, we focus on the task of procedural text understanding, which aims to comprehend such documents and track entities' states and locations during a process.

Procedural Text Understanding

DC-BERT: Decoupling Question and Document for Efficient Contextual Encoding

no code implementations28 Feb 2020 Yuyu Zhang, Ping Nie, Xiubo Geng, Arun Ramamurthy, Le Song, Daxin Jiang

Recent studies on open-domain question answering have achieved prominent performance improvement using pre-trained language models such as BERT.

Natural Questions Open-Domain Question Answering +1

A New Probabilistic Model for Rank Aggregation

no code implementations NeurIPS 2010 Tao Qin, Xiubo Geng, Tie-Yan Liu

To avoid these limitations, in this paper, we propose a new model, which is defined with a coset-permutation distance, and models the generation of a permutation as a stagewise process.

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