Search Results for author: Weiqi Wang

Found 37 papers, 23 papers with code

GoldCoin: Grounding Large Language Models in Privacy Laws via Contextual Integrity Theory

no code implementations17 Jun 2024 Wei Fan, Haoran Li, Zheye Deng, Weiqi Wang, Yangqiu Song

Privacy issues arise prominently during the inappropriate transmission of information between entities.

MIND: Multimodal Shopping Intention Distillation from Large Vision-language Models for E-commerce Purchase Understanding

1 code implementation15 Jun 2024 Baixuan Xu, Weiqi Wang, Haochen Shi, Wenxuan Ding, Huihao Jing, Tianqing Fang, Jiaxin Bai, Long Chen, Yangqiu Song

Improving user experience and providing personalized search results in E-commerce platforms heavily rely on understanding purchase intention.

IntentionQA: A Benchmark for Evaluating Purchase Intention Comprehension Abilities of Language Models in E-commerce

1 code implementation14 Jun 2024 Wenxuan Ding, Weiqi Wang, Sze Heng Douglas Kwok, Minghao Liu, Tianqing Fang, Jiaxin Bai, Junxian He, Yangqiu Song

Enhancing Language Models' (LMs) ability to understand purchase intentions in E-commerce scenarios is crucial for their effective assistance in various downstream tasks.

Multiple-choice Question Answering

MARS: Benchmarking the Metaphysical Reasoning Abilities of Language Models with a Multi-task Evaluation Dataset

1 code implementation4 Jun 2024 Weiqi Wang, Yangqiu Song

To enable Large Language Models (LLMs) to function as conscious agents with generalizable reasoning capabilities, it is crucial that they possess the reasoning ability to comprehend situational changes (transitions) in distribution triggered by environmental factors or actions from other agents.

Benchmarking

Physics-informed deep learning and compressive collocation for high-dimensional diffusion-reaction equations: practical existence theory and numerics

1 code implementation3 Jun 2024 Simone Brugiapaglia, Nick Dexter, Samir Karam, Weiqi Wang

On the forefront of scientific computing, Deep Learning (DL), i. e., machine learning with Deep Neural Networks (DNNs), has emerged a powerful new tool for solving Partial Differential Equations (PDEs).

Towards Subgraph Isomorphism Counting with Graph Kernels

no code implementations13 May 2024 Xin Liu, Weiqi Wang, Jiaxin Bai, Yangqiu Song

Subgraph isomorphism counting is known as #P-complete and requires exponential time to find the accurate solution.

Graph Classification Representation Learning

Machine Unlearning: A Comprehensive Survey

no code implementations13 May 2024 Weiqi Wang, Zhiyi Tian, Shui Yu

We categorize current unlearning methods into four scenarios: centralized unlearning, distributed and irregular data unlearning, unlearning verification, and privacy and security issues in unlearning.

Machine Unlearning

Text-Tuple-Table: Towards Information Integration in Text-to-Table Generation via Global Tuple Extraction

2 code implementations22 Apr 2024 Zheye Deng, Chunkit Chan, Weiqi Wang, Yuxi Sun, Wei Fan, Tianshi Zheng, Yauwai Yim, Yangqiu Song

The task of condensing large chunks of textual information into concise and structured tables has gained attention recently due to the emergence of Large Language Models (LLMs) and their potential benefit for downstream tasks, such as text summarization and text mining.

Text Summarization

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.

Common 7B Language Models Already Possess Strong Math Capabilities

1 code implementation7 Mar 2024 Chen Li, Weiqi Wang, Jingcheng Hu, Yixuan Wei, Nanning Zheng, Han Hu, Zheng Zhang, Houwen Peng

This paper shows that the LLaMA-2 7B model with common pre-training already exhibits strong mathematical abilities, as evidenced by its impressive accuracy of 97. 7% and 72. 0% on the GSM8K and MATH benchmarks, respectively, when selecting the best response from 256 random generations.

GSM8K Math

MIKO: Multimodal Intention Knowledge Distillation from Large Language Models for Social-Media Commonsense Discovery

no code implementations28 Feb 2024 Feihong Lu, Weiqi Wang, Yangyifei Luo, Ziqin Zhu, Qingyun Sun, Baixuan Xu, Haochen Shi, Shiqi Gao, Qian Li, Yangqiu Song, JianXin Li

However, understanding the intention behind social media posts remains challenging due to the implicitness of intentions in social media posts, the need for cross-modality understanding of both text and images, and the presence of noisy information such as hashtags, misspelled words, and complicated abbreviations.

Knowledge Distillation Language Modelling +2

EntailE: Introducing Textual Entailment in Commonsense Knowledge Graph Completion

no code implementations15 Feb 2024 Ying Su, Tianqing Fang, Huiru Xiao, Weiqi Wang, Yangqiu Song, Tong Zhang, Lei Chen

In this paper, we propose to adopt textual entailment to find implicit entailment relations between CSKG nodes, to effectively densify the subgraph connecting nodes within the same conceptual class, which indicates a similar level of plausibility.

graph construction Knowledge Graph Embedding +1

CANDLE: Iterative Conceptualization and Instantiation Distillation from Large Language Models for Commonsense Reasoning

2 code implementations14 Jan 2024 Weiqi Wang, Tianqing Fang, Chunyang Li, Haochen Shi, Wenxuan Ding, Baixuan Xu, Zhaowei Wang, Jiaxin Bai, Xin Liu, Jiayang Cheng, Chunkit Chan, Yangqiu Song

The sequential process of conceptualization and instantiation is essential to generalizable commonsense reasoning as it allows the application of existing knowledge to unfamiliar scenarios.

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

Chain-of-Choice Hierarchical Policy Learning for Conversational Recommendation

1 code implementation27 Oct 2023 Wei Fan, Weijia Zhang, Weiqi Wang, Yangqiu Song, Hao liu

Conversational Recommender Systems (CRS) illuminate user preferences via multi-round interactive dialogues, ultimately navigating towards precise and satisfactory recommendations.

Attribute Hierarchical Reinforcement Learning +1

Gold: A Global and Local-aware Denoising Framework for Commonsense Knowledge Graph Noise Detection

1 code implementation18 Oct 2023 Zheye Deng, Weiqi Wang, Zhaowei Wang, Xin Liu, Yangqiu Song

Commonsense Knowledge Graphs (CSKGs) are crucial for commonsense reasoning, yet constructing them through human annotations can be costly.

Denoising Knowledge Graphs +1

QADYNAMICS: Training Dynamics-Driven Synthetic QA Diagnostic for Zero-Shot Commonsense Question Answering

1 code implementation17 Oct 2023 Haochen Shi, Weiqi Wang, Tianqing Fang, Baixuan Xu, Wenxuan Ding, Xin Liu, Yangqiu Song

Zero-shot commonsense Question-Answering (QA) requires models to reason about general situations beyond specific benchmarks.

Question Answering

CAR: Conceptualization-Augmented Reasoner for Zero-Shot Commonsense Question Answering

1 code implementation24 May 2023 Weiqi Wang, Tianqing Fang, Wenxuan Ding, Baixuan Xu, Xin Liu, Yangqiu Song, Antoine Bosselut

The task of zero-shot commonsense question answering evaluates models on their capacity to reason about general scenarios beyond those presented in specific datasets.

Question Answering

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

CAT: A Contextualized Conceptualization and Instantiation Framework for Commonsense Reasoning

2 code implementations8 May 2023 Weiqi Wang, Tianqing Fang, Baixuan Xu, Chun Yi Louis Bo, Yangqiu Song, Lei Chen

Commonsense reasoning, aiming at endowing machines with a human-like ability to make situational presumptions, is extremely challenging to generalize.

ChatGPT Evaluation on Sentence Level Relations: A Focus on Temporal, Causal, and Discourse Relations

no code implementations28 Apr 2023 Chunkit Chan, Jiayang Cheng, Weiqi Wang, Yuxin Jiang, Tianqing Fang, Xin Liu, Yangqiu Song

This paper aims to quantitatively evaluate the performance of ChatGPT, an interactive large language model, on inter-sentential relations such as temporal relations, causal relations, and discourse relations.

Discourse Parsing In-Context Learning +6

CKBP v2: An Expert-Annotated Evaluation Set for Commonsense Knowledge Base Population

1 code implementation20 Apr 2023 Tianqing Fang, Quyet V. Do, Sehyun Choi, Weiqi Wang, Yangqiu Song

Populating Commonsense Knowledge Bases (CSKB) is an important yet hard task in NLP, as it tackles knowledge from external sources with unseen events and entities.

Knowledge Base Population

Rearrange Indoor Scenes for Human-Robot Co-Activity

no code implementations10 Mar 2023 Weiqi Wang, Zihang Zhao, Ziyuan Jiao, Yixin Zhu, Song-Chun Zhu, Hangxin Liu

We present an optimization-based framework for rearranging indoor furniture to accommodate human-robot co-activities better.

Understanding Physical Effects for Effective Tool-use

no code implementations30 Jun 2022 Zeyu Zhang, Ziyuan Jiao, Weiqi Wang, Yixin Zhu, Song-Chun Zhu, Hangxin Liu

We present a robot learning and planning framework that produces an effective tool-use strategy with the least joint efforts, capable of handling objects different from training.

Motion Planning regression +1

Acquiring and Modelling Abstract Commonsense Knowledge via Conceptualization

1 code implementation3 Jun 2022 Mutian He, Tianqing Fang, Weiqi Wang, Yangqiu Song

Conceptualization, or viewing entities and situations as instances of abstract concepts in mind and making inferences based on that, is a vital component in human intelligence for commonsense reasoning.

Knowledge Graphs

Compressive Fourier collocation methods for high-dimensional diffusion equations with periodic boundary conditions

no code implementations2 Jun 2022 Weiqi Wang, Simone Brugiapaglia

We also present numerical experiments that illustrate the accuracy and stability of the method for the approximation of sparse and compressible solutions.

Compressive Sensing

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

Numerical solution for the stress near a hole with corners in an infinite plate under biaxial loading

no code implementations10 Feb 2020 Weiqi Wang, Brian J. Spencer

The resulting boundary integral equations are solved numerically using a Chebyshev collocation method which is augmented by a fractional power term, derived by asymptotic analysis of the corner region, to resolve stress singularities at corners of the hole.

Analysis of PDEs Numerical Analysis Numerical Analysis

Cross-Sentence Grammatical Error Correction

1 code implementation ACL 2019 Shamil Chollampatt, Weiqi Wang, Hwee Tou Ng

Automatic grammatical error correction (GEC) research has made remarkable progress in the past decade.

Decoder Grammatical Error Correction +1

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