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Yuncheng Hua

11 accepted papers

2025

Beyond Words: Integrating Theory of Mind into Conversational Agents for Human-Like Belief, Desire, and Intention Alignment

ACL 2025finding

Natural language interaction has long served as the primary medium through which humans exchange ideas. A key enabler of this communication is the human capacity for Theory of Mind (ToM)—the ability to infer and align with the mental states of others. ToM is usually modeled as components of desires,…

2025

Boosting Resilience of Large Language Models through Causality-Driven Robust Optimization

NeurIPS 2025poster

Large language models (LLMs) have achieved remarkable achievements across diverse applications; however, they remain plagued by spurious correlations and the generation of hallucinated content. Despite extensive efforts to enhance the resilience of LLMs, existing approaches either rely on indiscrimi…

Cited by 0SourceScholar
2025

SCAR: Data Selection via Style Consistency-Aware Response Ranking for Efficient Instruction-Tuning of Large Language Models

ACL 2025long

Recent studies emphasize that manually ensuring a consistent response style and maintaining high data quality in training sets can significantly improve the performance of fine-tuned Large Language Models (LLMs) while reducing the number of training examples needed. However, the precise definition o…

2024

Assistive Large Language Model Agents for Socially-Aware Negotiation Dialogues

EMNLP 2024finding

We develop assistive agents based on Large Language Models (LLMs) that aid interlocutors in business negotiations.Specifically, we simulate business negotiations by letting two LLM-based agents engage in role play. A third LLM acts as a remediator agent to rewrite utterances violating norms for impr…

2024

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

EMNLP 2024finding

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 emotions in target domains are dramatically different than those in source domains, despite the distributions of emotional…

2024

CoTKR: Chain-of-Thought Enhanced Knowledge Rewriting for Complex Knowledge Graph Question Answering

EMNLP 2024main

Recent studies have explored the use of Large Language Models (LLMs) with Retrieval Augmented Generation (RAG) for Knowledge Graph Question Answering (KGQA). They typically require rewriting retrieved subgraphs into natural language formats comprehensible to LLMs. However, when tackling complex ques…

2024

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

ACL 2024long

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 generalization, where a model is trained on one source domain and tested on multiple target domains that are unseen during t…

2024

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

NAACL 2024findings

Norm violations occur when individuals fail to conform to culturally accepted behaviors, which may lead to potential conflicts. Remediating norm violations requires social awareness and cultural sensitivity of the nuances at play. To equip interactive AI systems with a remediation ability, we offer…

2021

Towards Balanced Defect Prediction with Better Information Propagation

AAAI 2021technical

Defect prediction, the task of predicting the presence of defects in source code artifacts, has broad application in software development. Defect prediction faces two major challenges, label scarcity, where only a small percentage of code artifacts are labeled, and data imbalance, where the majority…

Cited by 2SourcePDFScholar
2020

Formal Query Building with Query Structure Prediction for Complex Question Answering over Knowledge Base

IJCAI 2020poster

Formal query building is an important part of complex question answering over knowledge bases. It aims to build correct executable queries for questions. Recent methods try to rank candidate queries generated by a state-transition strategy. However, this candidate generation strategy ignores the str…

2020

Retrieve, Program, Repeat: Complex Knowledge Base Question Answering via Alternate Meta-learning

IJCAI 2020poster

A compelling approach to complex question answering is to convert the question to a sequence of actions, which can then be executed on the knowledge base to yield the answer, aka the programmer-interpreter approach. Use similar training questions to the test question, meta-learning enables the progr…