2 citations · 3 across the 16 of their papers we have counts for
16 papers
Reference-Free Evaluation of Reasoning in Open-Ended Question Answering
Guneet Singh Kohli, Yuxiang Zhou, Michael Sejr Schlichtkrull +2
AI-generated answers in high-stakes domains are often fluent but difficult to verify, especially when they contain multi-step reasoning rather than a single final answer. We propos…
Human-Centric Topic Modeling with Goal-Prompted Contrastive Learning and Optimal Transport
Rui Wang, Yi Zheng, Dongxin Wang +5
Existing topic modeling methods, from LDA to recent neural and LLM-based approaches, which focus mainly on statistical coherence, often produce redundant or off-target topics that…
Compliance vs. Sensibility: On the Reasoning Controllability in Large Language Models
Xingwei Tan, Marco Valentino, Mahmud Elahi Akhter +3
Large Language Models (LLMs) acquire reasoning capabilities through shared inference patterns in pre-training data, which are further elicited via Chain-of-Thought (CoT). However,…
LiFT: How to Enable In-Context Learning for Longitudinal Modelling
Iqra Ali, Talia Tseriotou, Mahmud Elahi Akhter +2
Longitudinal NLP tasks such as mental health monitoring and stance evolution require modeling temporally ordered text to track persistence and detect change. Such tasks also suffer…
Chain Of Thought Compression: A Theoretical Analysis
Juncai Li, Ru Li, Yuxiang Zhou +2
Chain-of-Thought (CoT) has unlocked advanced reasoning abilities of Large Language Models (LLMs) with intermediate steps, yet incurs prohibitive computational costs due to generati…
Mobile-Agent-RAG: Driving Smart Multi-Agent Coordination with Contextual Knowledge Empowerment for Long-Horizon Mobile Automation
Yuxiang Zhou, Jichang Li, Yanhao Zhang +2
Mobile agents show immense potential, yet current state-of-the-art (SoTA) agents exhibit inadequate success rates on real-world, long-horizon, cross-application tasks. We attribute…
Red Teaming for Generative AI, Report on a Copyright-Focused Exercise Completed in an Academic Medical Center
James Wen, Sahil Nalawade, Zhiwei Liang +38
Background: Generative artificial intelligence (AI) deployment in academic medical settings raises copyright compliance concerns. Dana-Farber Cancer Institute implemented GPT4DFCI,…
Modeling Subjectivity in Cognitive Appraisal with Language Models
Yuxiang Zhou, Hainiu Xu, Desmond C. Ong +3
As the utilization of language models in interdisciplinary, human-centered studies grow, expectations of their capabilities continue to evolve. Beyond excelling at conventional tas…
EnigmaToM: Improve LLMs' Theory-of-Mind Reasoning Capabilities with Neural Knowledge Base of Entity States
Hainiu Xu, Siya Qi, Jiazheng Li +4
Theory-of-Mind (ToM), the ability to infer others' perceptions and mental states, is fundamental to human interaction but remains challenging for Large Language Models (LLMs). Whil…
Two Heads Are Better Than One: Dual-Model Verbal Reflection at Inference-Time
Jiazheng Li, Yuxiang Zhou, Junru Lu +4
Although preference optimization methods have improved reasoning performance in Large Language Models (LLMs), they often lack transparency regarding why one reasoning outcome is pr…
Causal Fine-Tuning under Latent Confounded Shift
Jialin Yu, Yuxiang Zhou, Haoxuan Li +6
Adapting to latent confounded shift remains a core challenge in modern AI. This setting is driven by hidden variables that induce spurious correlations between inputs and outputs d…
Calibrating LLMs with Preference Optimization on Thought Trees for Generating Rationale in Science Question Scoring
Jiazheng Li, Hainiu Xu, Zhaoyue Sun +4
Generating rationales that justify scoring decisions has been a promising way to facilitate explainability in automated scoring systems. However, existing methods do not match the…
Cascading Large Language Models for Salient Event Graph Generation
Xingwei Tan, Yuxiang Zhou, Gabriele Pergola +1
Generating event graphs from long documents is challenging due to the inherent complexity of multiple tasks involved such as detecting events, identifying their relationships, and…
Set-Aligning Framework for Auto-Regressive Event Temporal Graph Generation
Xingwei Tan, Yuxiang Zhou, Gabriele Pergola +1
Event temporal graphs have been shown as convenient and effective representations of complex temporal relations between events in text. Recent studies, which employ pre-trained lan…
Large Language Models Fall Short: Understanding Complex Relationships in Detective Narratives
Runcong Zhao, Qinglin Zhu, Hainiu Xu +4
Existing datasets for narrative understanding often fail to represent the complexity and uncertainty of relationships in real-life social scenarios. To address this gap, we introdu…
The Mystery of In-Context Learning: A Comprehensive Survey on Interpretation and Analysis
Yuxiang Zhou, Jiazheng Li, Yanzheng Xiang +3
Understanding in-context learning (ICL) capability that enables large language models (LLMs) to excel in proficiency through demonstration examples is of utmost importance. This im…