Search Results for author: Wenjuan Han

Found 40 papers, 16 papers with code

SHARP: Search-Based Adversarial Attack for Structured Prediction

no code implementations Findings (NAACL) 2022 Liwen Zhang, Zixia Jia, Wenjuan Han, Zilong Zheng, Kewei Tu

Adversarial attack of structured prediction models faces various challenges such as the difficulty of perturbing discrete words, the sentence quality issue, and the sensitivity of outputs to small perturbations.

Adversarial Attack Dependency Parsing +4

Transformer in Touch: A Survey

no code implementations21 May 2024 Jing Gao, Ning Cheng, Bin Fang, Wenjuan Han

The Transformer model, initially achieving significant success in the field of natural language processing, has recently shown great potential in the application of tactile perception.

Object Recognition

Potential and Limitations of LLMs in Capturing Structured Semantics: A Case Study on SRL

no code implementations10 May 2024 Ning Cheng, Zhaohui Yan, ZiMing Wang, Zhijie Li, Jiaming Yu, Zilong Zheng, Kewei Tu, Jinan Xu, Wenjuan Han

Large Language Models (LLMs) play a crucial role in capturing structured semantics to enhance language understanding, improve interpretability, and reduce bias.

Semantic Role Labeling

MineLand: Simulating Large-Scale Multi-Agent Interactions with Limited Multimodal Senses and Physical Needs

1 code implementation28 Mar 2024 Xianhao Yu, Jiaqi Fu, Renjia Deng, Wenjuan Han

Our experiments demonstrate that the simulator, the corresponding benchmark, and the AI agent framework contribute to more ecological and nuanced collective behavior. The source code of MineLand and Alex is openly available at https://github. com/cocacola-lab/MineLand.

Scheduling valid

Towards Comprehensive Multimodal Perception: Introducing the Touch-Language-Vision Dataset

no code implementations14 Mar 2024 Ning Cheng, You Li, Jing Gao, Bin Fang, Jinan Xu, Wenjuan Han

Tactility provides crucial support and enhancement for the perception and interaction capabilities of both humans and robots.

Sentence

TransGPT: Multi-modal Generative Pre-trained Transformer for Transportation

no code implementations11 Feb 2024 Peng Wang, Xiang Wei, Fangxu Hu, Wenjuan Han

TransGPT-MM is finetuned on a multi-modal Transportation dataset (MTD) that we manually collected from three areas of the transportation domain: driving tests, traffic signs, and landmarks.

Language Modelling Large Language Model

TransportationGames: Benchmarking Transportation Knowledge of (Multimodal) Large Language Models

no code implementations9 Jan 2024 Xue Zhang, Xiangyu Shi, Xinyue Lou, Rui Qi, Yufeng Chen, Jinan Xu, Wenjuan Han

Large language models (LLMs) and multimodal large language models (MLLMs) have shown excellent general capabilities, even exhibiting adaptability in many professional domains such as law, economics, transportation, and medicine.

Benchmarking

CLOVA: A Closed-Loop Visual Assistant with Tool Usage and Update

no code implementations18 Dec 2023 Zhi Gao, Yuntao Du, Xintong Zhang, Xiaojian Ma, Wenjuan Han, Song-Chun Zhu, Qing Li

However, these methods often overlook the potential for continual learning, typically by freezing the utilized tools, thus limiting their adaptation to environments requiring new knowledge.

Continual Learning Question Answering +1

On the Robustness of Question Rewriting Systems to Questions of Varying Hardness

1 code implementation ACL 2022 Hai Ye, Hwee Tou Ng, Wenjuan Han

In conversational question answering (CQA), the task of question rewriting~(QR) in context aims to rewrite a context-dependent question into an equivalent self-contained question that gives the same answer.

Question Rewriting

Get the Ball Rolling: Alerting Autonomous Robots When to Help to Close the Healthcare Loop

no code implementations5 Nov 2023 Jiaxin Shen, Yanyao Liu, ZiMing Wang, Ziyuan Jiao, Yufeng Chen, Wenjuan Han

To facilitate the advancement of research in healthcare robots without human intervention or commands, we introduce the Autonomous Helping Challenge, along with a crowd-sourcing large-scale dataset.

A Quality-based Syntactic Template Retriever for Syntactically-controlled Paraphrase Generation

1 code implementation20 Oct 2023 Xue Zhang, Songming Zhang, Yunlong Liang, Yufeng Chen, Jian Liu, Wenjuan Han, Jinan Xu

Furthermore, for situations requiring multiple paraphrases for each source sentence, we design a Diverse Templates Search (DTS) algorithm, which can enhance the diversity between paraphrases without sacrificing quality.

Data Augmentation Paraphrase Generation +2

MMICL: Empowering Vision-language Model with Multi-Modal In-Context Learning

2 code implementations14 Sep 2023 Haozhe Zhao, Zefan Cai, Shuzheng Si, Xiaojian Ma, Kaikai An, Liang Chen, Zixuan Liu, Sheng Wang, Wenjuan Han, Baobao Chang

In this paper, we address the limitation above by 1) introducing vision-language Model with Multi-Modal In-Context Learning(MMICL), a new approach to allow the VLM to deal with multi-modal inputs efficiently; 2) proposing a novel context scheme to augment the in-context learning ability of the VLM; 3) constructing the Multi-modal In-Context Learning (MIC) dataset, designed to enhance the VLM's ability to understand complex multi-modal prompts.

Hallucination In-Context Learning +2

CollabKG: A Learnable Human-Machine-Cooperative Information Extraction Toolkit for (Event) Knowledge Graph Construction

1 code implementation3 Jul 2023 Xiang Wei, Yufeng Chen, Ning Cheng, Xingyu Cui, Jinan Xu, Wenjuan Han

In order to construct or extend entity-centric and event-centric knowledge graphs (KG and EKG), the information extraction (IE) annotation toolkit is essential.

graph construction Knowledge Graphs +3

Human-in-the-Loop through Chain-of-Thought

no code implementations10 Jun 2023 Zefan Cai, Baobao Chang, Wenjuan Han

While the emergence of powerful language models along with Chain-of-thought prompting has made automation more and more omnipresent, it sometimes demonstrates its weakness in long-term or multi-step logical reasoning.

Logical Reasoning

Enhance Reasoning Ability of Visual-Language Models via Large Language Models

no code implementations22 May 2023 Yueting Yang, Xintong Zhang, Wenjuan Han

Thinking stage combines the image information and task description as the prompt of the LLM, inference with the rationals.

Language Modelling Large Language Model

Towards Understanding and Improving Knowledge Distillation for Neural Machine Translation

1 code implementation14 May 2023 Songming Zhang, Yunlong Liang, Shuaibo Wang, Wenjuan Han, Jian Liu, Jinan Xu, Yufeng Chen

In this work, we first unravel this mystery from an empirical perspective and show that the knowledge comes from the top-1 predictions of teachers, which also helps us build a potential connection between word- and sequence-level KD.

Knowledge Distillation Machine Translation +2

IntentQA: Context-aware Video Intent Reasoning

1 code implementation ICCV 2023 Jiapeng Li, Ping Wei, Wenjuan Han, Lifeng Fan

In this paper, we propose a novel task IntentQA, a special VideoQA task focusing on video intent reasoning, which has become increasingly important for AI with its advantages in equipping AI agents with the capability of reasoning beyond mere recognition in daily tasks.

Contrastive Learning

Modeling Instance Interactions for Joint Information Extraction with Neural High-Order Conditional Random Field

1 code implementation17 Dec 2022 Zixia Jia, Zhaohui Yan, Wenjuan Han, Zilong Zheng, Kewei Tu

Prior works on joint Information Extraction (IE) typically model instance (e. g., event triggers, entities, roles, relations) interactions by representation enhancement, type dependencies scoring, or global decoding.

Decoder Variational Inference

To think inside the box, or to think out of the box? Scientific discovery via the reciprocation of insights and concepts

no code implementations1 Dec 2022 Yu-Zhe Shi, Manjie Xu, Wenjuan Han, Yixin Zhu

If scientific discovery is one of the main driving forces of human progress, insight is the fuel for the engine, which has long attracted behavior-level research to understand and model its underlying cognitive process.

On the Complexity of Bayesian Generalization

1 code implementation20 Nov 2022 Yu-Zhe Shi, Manjie Xu, John E. Hopcroft, Kun He, Joshua B. Tenenbaum, Song-Chun Zhu, Ying Nian Wu, Wenjuan Han, Yixin Zhu

Specifically, at the $representational \ level$, we seek to answer how the complexity varies when a visual concept is mapped to the representation space.

Attribute

VGStore: A Multimodal Extension to SPARQL for Querying RDF Scene Graph

1 code implementation7 Sep 2022 Yanzeng Li, Zilong Zheng, Wenjuan Han, Lei Zou

Semantic Web technology has successfully facilitated many RDF models with rich data representation methods.

Relational Reasoning Semantic Similarity +1

Diversity-Driven Combination for Grammatical Error Correction

no code implementations28 Oct 2021 Wenjuan Han, Hwee Tou Ng

However, most existing state-of-the-art GEC approaches are based on similar sequence-to-sequence neural networks, so the gains are limited from combining the outputs of component systems similar to one another.

Grammatical Error Correction

Robust Transfer Learning with Pretrained Language Models through Adapters

no code implementations ACL 2021 Wenjuan Han, Bo Pang, YingNian Wu

Transfer learning with large pretrained transformer-based language models like BERT has become a dominating approach for most NLP tasks.

Adversarial Attack Adversarial Robustness +1

Adapting Unsupervised Syntactic Parsing Methodology for Discourse Dependency Parsing

no code implementations ACL 2021 Liwen Zhang, Ge Wang, Wenjuan Han, Kewei Tu

In this paper, we propose a simple yet effective method to adapt unsupervised syntactic dependency parsing methodology for unsupervised discourse dependency parsing.

Dependency Parsing Discourse Parsing

Unsupervised Natural Language Parsing (Introductory Tutorial)

no code implementations EACL 2021 Kewei Tu, Yong Jiang, Wenjuan Han, Yanpeng Zhao

Unsupervised parsing learns a syntactic parser from training sentences without parse tree annotations.

Constrained Text Generation with Global Guidance -- Case Study on CommonGen

no code implementations12 Mar 2021 Yixian Liu, Liwen Zhang, Wenjuan Han, Yue Zhang, Kewei Tu

We focus on CommonGen, the task of generating text based on a set of concepts, as a representative task of constrained text generation.

Common Sense Reasoning reinforcement-learning +3

ToHRE: A Top-Down Classification Strategy with Hierarchical Bag Representation for Distantly Supervised Relation Extraction

no code implementations COLING 2020 Erxin Yu, Wenjuan Han, Yuan Tian, Yi Chang

Distantly Supervised Relation Extraction (DSRE) has proven to be effective to find relational facts from texts, but it still suffers from two main problems: the wrong labeling problem and the long-tail problem.

Classification Relation +1

Second-Order Unsupervised Neural Dependency Parsing

1 code implementation COLING 2020 Songlin Yang, Yong Jiang, Wenjuan Han, Kewei Tu

Inspired by second-order supervised dependency parsing, we proposed a second-order extension of unsupervised neural dependency models that incorporate grandparent-child or sibling information.

Dependency Grammar Induction

Adversarial Attack and Defense of Structured Prediction Models

1 code implementation EMNLP 2020 Wenjuan Han, Liwen Zhang, Yong Jiang, Kewei Tu

To address these problems, we propose a novel and unified framework that learns to attack a structured prediction model using a sequence-to-sequence model with feedbacks from multiple reference models of the same structured prediction task.

Adversarial Attack Dependency Parsing +3

Multilingual Grammar Induction with Continuous Language Identification

no code implementations IJCNLP 2019 Wenjuan Han, Ge Wang, Yong Jiang, Kewei Tu

The key to multilingual grammar induction is to couple grammar parameters of different languages together by exploiting the similarity between languages.

Language Identification

A Regularization-based Framework for Bilingual Grammar Induction

no code implementations IJCNLP 2019 Yong Jiang, Wenjuan Han, Kewei Tu

Grammar induction aims to discover syntactic structures from unannotated sentences.

Enhancing Unsupervised Generative Dependency Parser with Contextual Information

no code implementations ACL 2019 Wenjuan Han, Yong Jiang, Kewei Tu

In this paper, we propose a novel probabilistic model called discriminative neural dependency model with valence (D-NDMV) that generates a sentence and its parse from a continuous latent representation, which encodes global contextual information of the generated sentence.

Constituency Grammar Induction Dependency Grammar Induction +2

Dependency Grammar Induction with Neural Lexicalization and Big Training Data

no code implementations EMNLP 2017 Wenjuan Han, Yong Jiang, Kewei Tu

We study the impact of big models (in terms of the degree of lexicalization) and big data (in terms of the training corpus size) on dependency grammar induction.

Dependency Grammar Induction

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