collaborators

24 papers

cs.LG2026

MM-PoisonRAG: Disrupting Multimodal RAG with Local and Global Poisoning Attacks

Hyeonjeong Ha, Qiusi Zhan, Jeonghwan Kim +6

Retrieval-augmented generation (RAG) has become a common practice in multimodal large language models (MLLM) to enhance factual grounding and reduce hallucination. Yet, its relianc…

cs.CV2026

OpenVLThinkerV2: A Generalist Multimodal Reasoning Model for Multi-domain Visual Tasks

Wenbo Hu, Xin Chen, Yan Gao-Tian +3

Group Relative Policy Optimization (GRPO) has emerged as the de facto Reinforcement Learning (RL) objective driving recent advancements in Multimodal Large Language Models. However…

cs.CL2026

Beyond Facts: Benchmarking Distributional Reading Comprehension in Large Language Models

Pei-Fu Guo, Ya-An Tsai, Chun-Chia Hsu +6

While most reading comprehension benchmarks for LLMs focus on factual information that can be answered by localizing specific textual evidence, many real-world tasks require unders…

cs.CL2026

LiveCLKTBench: Towards Reliable Evaluation of Cross-Lingual Knowledge Transfer in Multilingual LLMs

Pei-Fu Guo, Yun-Da Tsai, Chun-Chia Hsu +6

Evaluating cross-lingual knowledge transfer in large language models is challenging, as correct answers in a target language may arise either from genuine transfer or from prior ex…

cs.CL2026

SemEval-2026 Task 3: Dimensional Aspect-Based Sentiment Analysis (DimABSA)

Liang-Chih Yu, Jonas Becker, Shamsuddeen Hassan Muhammad +14

We present the SemEval-2026 shared task on Dimensional Aspect-Based Sentiment Analysis (DimABSA), which improves traditional ABSA by modeling sentiment along valence-arousal (VA) d…

cs.LG2026

TaoBench: Do Automated Theorem Prover LLMs Generalize Beyond MathLib?

Alexander K Taylor, Junyi Zhang, Ethan Ji +10

Automated theorem proving (ATP) benchmarks largely consist of problems formalized in MathLib, so current ATP training and evaluation are heavily biased toward MathLib's definitiona…