collaborators

7 papers

eess.AS2026

SMC-ITA: Sequential Monte Carlo Inference-Time Alignment for Video-to-Audio Generation

Haoyu Zhang, Yuta Oshima, Xingjian Du +4

Video-to-audio (V2A) generation must jointly satisfy audiovisual alignment, semantic consistency, temporal synchronization, and perceptual quality. While prior work has mainly focu…

cs.CV2026

JMed48k: A Multi-Profession Japanese Medical Licensing Benchmark for Vision-Language Model Evaluation

Yue Xun, Junyu Liu, Qian Niu +10

We introduce JMed48k, a multi-profession Japanese healthcare licensing benchmark for evaluating vision-language models. Built from official PDF materials released by the Japanese M…

cs.CL2026

Omanic: Towards Step-wise Evaluation of Multi-hop Reasoning in Large Language Models

Xiaojie Gu, Sherry T. Tong, Aosong Feng +8

Evaluating the reasoning abilities of large language models (LLMs) solely from final answers can obscure failures in intermediate steps, especially in multi-hop QA benchmarks witho…

cs.CL2026

Med-CoReasoner: Reducing Language Disparities in Medical Reasoning via Language-Informed Co-Reasoning

Fan Gao, Sherry T. Tong, Jiwoong Sohn +11

While reasoning-enhanced large language models perform strongly on English medical tasks, a persistent multilingual gap remains, with substantially weaker reasoning in local langua…

cs.CL2026

From Chains to Graphs: Self-Structured Reasoning for General-Domain LLMs

Yingjian Chen, Haoran Liu, Yinhong Liu +7

Large Language Models (LLMs) show strong reasoning ability in open-domain question answering, yet their reasoning processes are typically linear and often logically inconsistent. I…

cs.CL2026

Investigating the Multilingual Calibration Effects of Language Model Instruction-Tuning

Jerry Huang, Peng Lu, Qiuhao Zeng +5

Ensuring that deep learning models are well-calibrated in terms of their predictive uncertainty is essential in maintaining their trustworthiness and reliability, yet despite incre…