collaborators

10 papers

cs.CV2026

Beyond Relevance: Bayesian Evidence Acquisition for Agentic Whole-Slide Image Reasoning

Bryan Wong, Xun Xu, Huazhu Fu +2

Whole-slide image (WSI) reasoning requires an agent to sequentially acquire visual evidence before answering a diagnostic question. Existing training-free agentic frameworks formul…

cs.AI2026

InfoDensity: Rewarding Information-Dense Traces for Efficient Reasoning

Chengwei Wei, Jung-jae Kim, Longyin Zhang +2

Large Language Models (LLMs) with extended reasoning capabilities often generate verbose and redundant reasoning traces, incurring unnecessary computational cost. While existing re…

cs.CL2026

SagaQA: A Multi-hop Reasoning Benchmark for Long-form Narrative Understanding in TV Series

Galann Pennec, Zhengyuan Liu, Nicholas Asher +2

We introduce SagaQA, a long-form video benchmark for multi-hop reasoning over full-length TV series. Existing video reasoning benchmarks often emphasize local understanding of adja…

cs.CL2026

The Deliberative Illusion: Diagnosing Factual Attrition and Stance Homogenization in Multi-Agent LLM Deliberation

Herun Wan, Jiaying Wu, Minnan Luo +4

Multi-agent LLM systems often treat consensus as evidence of successful interaction. For deliberative problems, however, reliability depends on whether agents preserve the facts an…

cs.CL2026

MeMo: Memory as a Model

Ryan Wei Heng Quek, Sanghyuk Lee, Alfred Wei Lun Leong +6

Large language models (LLMs) achieve strong performance across a wide range of tasks, but remain frozen after pretraining until subsequent updates. Many real-world applications req…

cs.LG2026

Is Data Shapley Not Better than Random in Data Selection? Ask NASH

Xiao Tian, Jue Fan, Rachael Hwee Ling Sim +3

Data selection studies the problem of identifying high-quality subsets of training data. While some existing works have considered selecting the subset of data with top- Data Sh…