1 citations · 3 across the 21 of their papers we have counts for
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BeDiscovER: The Benchmark of Discourse Understanding in the Era of Reasoning Language Models
Chuyuan Li, Giuseppe Carenini
We introduce BeDiscovER (Benchmark of Discourse Understanding in the Era of Reasoning Language Models), an up-to-date, comprehensive suite for evaluating the discourse-level knowle…
CEMTM: Contextual Embedding-based Multimodal Topic Modeling
Amirhossein Abaskohi, Raymond Li, Chuyuan Li +2
We introduce CEMTM, a context-enhanced multimodal topic model designed to infer coherent and interpretable topic structures from both short and long documents containing text and i…
ChartGaze: Enhancing Chart Understanding in LVLMs with Eye-Tracking Guided Attention Refinement
Ali Salamatian, Amirhossein Abaskohi, Wan-Cyuan Fan +3
Charts are a crucial visual medium for communicating and representing information. While Large Vision-Language Models (LVLMs) have made progress on chart question answering (CQA),…
Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization
Chuyuan Li, Austin Xu, Shafiq Joty +1
A key challenge in Multi-Document Summarization (MDS) is effectively integrating information from multiple sources while maintaining coherence and topical relevance. While Large La…
Infusing Theory of Mind into Socially Intelligent LLM Agents
EunJeong Hwang, Yuwei Yin, Giuseppe Carenini +2
Theory of Mind (ToM)-an understanding of the mental states of others-is a key aspect of human social intelligence, yet, chatbots and LLM-based social agents do not typically integr…
Delta-KNN: Improving Demonstration Selection in In-Context Learning for Alzheimer's Disease Detection
Chuyuan Li, Raymond Li, Thalia S. Field +1
Alzheimer's Disease (AD) is a progressive neurodegenerative disorder that leads to dementia, and early intervention can greatly benefit from analyzing linguistic abnormalities. In…
AgentAda: Skill-Adaptive Data Analytics for Tailored Insight Discovery
Amirhossein Abaskohi, Amrutha Varshini Ramesh, Shailesh Nanisetty +6
We introduce AgentAda, the first LLM-powered analytics agent that can learn and use new analytics skills to extract more specialized insights. Unlike existing methods that require…
SWI: Speaking with Intent in Large Language Models
Yuwei Yin, EunJeong Hwang, Giuseppe Carenini
Intent, typically clearly formulated and planned, functions as a cognitive framework for communication and problem-solving. This paper introduces the concept of Speaking with Inten…
Multi2: Multi-Agent Test-Time Scalable Framework for Multi-Document Processing
Juntai Cao, Xiang Zhang, Raymond Li +4
Recent advances in test-time scaling have shown promising results in improving Large Language Model (LLM) performance through strategic computation allocation during inference. Whi…
Improving Language Models with Intentional Analysis
Yuwei Yin, Giuseppe Carenini
Intent, a critical cognitive notion and mental state, is ubiquitous in human communication and problem-solving. Accurately understanding the underlying intent behind questions is i…