8 papers
Overview of SHROOM-Visions 2026: A Shared Task on Hallucination Detection in Large Vision-Language Models
Raúl Vázquez, Aman Sinha, Chuyuan Li +12
In 2026, we held the fourth iteration of the SHROOM Shared Task series: SHROOM-Visions (\textbf{S}hared-task on \textbf{H}allucinations and \textbf{R}elated \textbf{O}bservable \te…
Can Humans Dream of Electric Sheep? Human-Written Samples for Fine-Grained Vision-and-Language Hallucination Benchmarking
Timothee Mickus, Claudio Savelli, Eduardo Calò +10
In an age of rapid model turnover, how do we make hallucination evaluation more perennial? We explore whether human-written hallucination samples could take the place of model-gene…
The Illusion of Multi-Agent Advantage
Prathyusha Jwalapuram, Hehai Lin, Chuyuan Li +7
Prevailing wisdom posits that Multi-Agent Systems (MAS) are superior to Single-Agent Systems (SAS), citing advantages like context protection, parallel processing and distributed d…
IntentGrasp: A Comprehensive Benchmark for Intent Understanding
Yuwei Yin, Chuyuan Li, Giuseppe Carenini
Accurately understanding the intent behind speech, conversation, and writing is crucial to the development of helpful Large Language Model (LLM) assistants. This paper introduces I…
Improving Topic Modeling by Distilling Soft Labels from Language Models
Raymond Li, Amirhossein Abaskohi, Chuyuan Li +2
Traditional neural topic models are typically optimized by reconstructing the document's Bag-of-Words (BoW) representations, overlooking contextual information and struggling with…
Confabulations from ACL Publications (CAP): A Dataset for Scientific Hallucination Detection
Federica Gamba, Aman Sinha, Timothee Mickus +12
We introduce the CAP (Confabulations from ACL Publications) dataset, a multilingual resource for studying hallucinations in large language models (LLMs) within scientific text gene…
Discourse Structure Extraction from Pre-Trained and Fine-Tuned Language Models in Dialogues
Chuyuan Li, Patrick Huber, Wen Xiao +3
Discourse processing suffers from data sparsity, especially for dialogues. As a result, we explore approaches to build discourse structures for dialogues, based on attention matric…
Multi-Task Learning for Depression Detection in Dialogs
Chuyuan Li, Chloé Braud, Maxime Amblard
Depression is a serious mental illness that impacts the way people communicate, especially through their emotions, and, allegedly, the way they interact with others. This work exam…