collaborators

13 papers

cs.CL2026

ConstructCIE: A Dataset for Extracting Causal Information from Construction Accident Narratives

Hung Nguyen, Jaehoon Lee, Namgyun Kim +1

Construction accident narratives contain rich causal information, but the evidence is often implicit, long-span, and distributed. We introduce ConstructCIE, a manually annotated da…

cs.CL2026

What's Missing in Vision-Language Models? Probing Their Struggles with Causal Order Reasoning

Zhaotian Weng, Haoxuan Li, Xin Eric Wang +2

Despite the impressive performance of vision-language models (VLMs) on downstream tasks, their ability to understand and reason about causal relationships in visual inputs remains…

cs.CV2026

Look Before You Zoom: Adaptive Routing for the Resolution-Context Trade-off in Visual RAG

Oanh N. Tran, Thanh Quoc Hung Le, Oscar Chew +2

Vision-Language Models (VLMs) struggle as query-relevant objects become smaller. To address this, recent training-free approaches dynamically retrieve and zoom into local image reg…

cs.CL2026

TRACES: Proactive Safety Auditing for Multi-Turn LLM Agents via Trajectory-State Modeling

Jiaqian Li, Yanshu Li, Boxuan Zhang +2

LLM agents increasingly operate through multi-turn tool use and environment interaction, where safety risks often emerge from intermediate steps long before they surface in the fin…

cs.CV2026

Pop-Up Distractions Reveal Bag-of-Events Behavior in Video Large Language Models

Oscar Chew, Serhii Honcharenko, Qian-Hui Chen +4

A key capability for video understanding is reliably linking subjects to events across time, yet whether Video Large Language Models (VideoLLMs) actually achieve this remains uncle…

cs.LG2026

When Correct Demonstrations Hurt: Rethinking the Role of Exemplars in In-Context Learning

Chenghao Qiu, Chunli Peng, Yufeng Yang +2

In-context learning (ICL) is often motivated by the intuition that demonstrations help because they provide correct input-output examples. However, we reveal a counterintuitive phe…