activity
20222025
most citedLet's Negotiate! A Survey of Negotiation Dialogue Systems

8 citations · 16 across the 14 of their papers we have counts for

collaborators

14 papers

cs.CL2025

IRIS: An Iterative and Integrated Framework for Verifiable Causal Discovery in the Absence of Tabular Data

Tao Feng, Lizhen Qu, Niket Tandon +1

Causal discovery is fundamental to scientific research, yet traditional statistical algorithms face significant challenges, including expensive data collection, redundant computati…

cs.CV2025

Physics-Grounded Motion Forecasting via Equation Discovery for Trajectory-Guided Image-to-Video Generation

Tao Feng, Xianbing Zhao, Zhenhua Chen +4

Recent advances in diffusion-based and autoregressive video generation models have achieved remarkable visual realism. However, these models typically lack accurate physical alignm…

cs.AI2025

ACCESS : A Benchmark for Abstract Causal Event Discovery and Reasoning

Vy Vo, Lizhen Qu, Tao Feng +6

Identifying cause-and-effect relationships is critical to understanding real-world dynamics and ultimately causal reasoning. Existing methods for identifying event causality in NLP…

cs.LG2024

Learning in Order! A Sequential Strategy to Learn Invariant Features for Multimodal Sentiment Analysis

Xianbing Zhao, Lizhen Qu, Tao Feng +2

This work proposes a novel and simple sequential learning strategy to train models on videos and texts for multimodal sentiment analysis. To estimate sentiment polarities on unseen…

cs.CL2024★ 3 cited

On the Reliability of Large Language Models for Causal Discovery

Tao Feng, Lizhen Qu, Niket Tandon +3

This study investigates the efficacy of Large Language Models (LLMs) in causal discovery. Using newly available open-source LLMs, OLMo and BLOOM, which provide access to their pre-…

cs.CL2024★ 1 cited

CausalScore: An Automatic Reference-Free Metric for Assessing Response Relevance in Open-Domain Dialogue Systems

Tao Feng, Lizhen Qu, Xiaoxi Kang +1

Automatically evaluating the quality of responses in open-domain dialogue systems is a challenging but crucial task. Current evaluation metrics often fail to align with human judgm…

cs.CL2024★ 2 cited

Causal Discovery Inspired Unsupervised Domain Adaptation for Emotion-Cause Pair Extraction

Yuncheng Hua, Yujin Huang, Shuo Huang +5

This paper tackles the task of emotion-cause pair extraction in the unsupervised domain adaptation setting. The problem is challenging as the distributions of the events causing em…

cs.CL2024

IMO: Greedy Layer-Wise Sparse Representation Learning for Out-of-Distribution Text Classification with Pre-trained Models

Tao Feng, Lizhen Qu, Zhuang Li +3

Machine learning models have made incredible progress, but they still struggle when applied to examples from unseen domains. This study focuses on a specific problem of domain gene…

cs.CL2024

RENOVI: A Benchmark Towards Remediating Norm Violations in Socio-Cultural Conversations

Haolan Zhan, Zhuang Li, Xiaoxi Kang +14

Norm violations occur when individuals fail to conform to culturally accepted behaviors, which may lead to potential conflicts. Remediating norm violations requires social awarenes…

cs.CL2024★ 1 cited

Let's Negotiate! A Survey of Negotiation Dialogue Systems

Haolan Zhan, Yufei Wang, Tao Feng +7

Negotiation is a crucial ability in human communication. Recently, there has been a resurgent research interest in negotiation dialogue systems, whose goal is to create intelligent…

cs.CL2024

SADAS: A Dialogue Assistant System Towards Remediating Norm Violations in Bilingual Socio-Cultural Conversations

Yuncheng Hua, Zhuang Li, Linhao Luo +8

In today's globalized world, bridging the cultural divide is more critical than ever for forging meaningful connections. The Socially-Aware Dialogue Assistant System (SADAS) is our…

cs.CL2023★ 1 cited

SocialDial: A Benchmark for Socially-Aware Dialogue Systems

Haolan Zhan, Zhuang Li, Yufei Wang +10

Dialogue systems have been widely applied in many scenarios and are now more powerful and ubiquitous than ever before. With large neural models and massive available data, current…

cs.CL2023

Less is More: Mitigate Spurious Correlations for Open-Domain Dialogue Response Generation Models by Causal Discovery

Tao Feng, Lizhen Qu, Gholamreza Haffari

In this paper, we conduct the first study on spurious correlations for open-domain response generation models based on a corpus CGDIALOG curated in our work. The cur rent models in…

cs.CL2022★ 8 cited

Let's Negotiate! A Survey of Negotiation Dialogue Systems

Haolan Zhan, Yufei Wang, Tao Feng +5

Negotiation is one of the crucial abilities in human communication, and there has been a resurgent research interest in negotiation dialogue systems recently, which goal is to empo…