collaborators

10 papers

cs.LG2026

C-MORAL: Controllable Multi-Objective Molecular Optimization with Reinforcement Alignment for LLMs

Rui Gao, Youngseung Jeon, Swastik Roy +2

Large language models (LLMs) show promise for molecular optimization, but aligning them with selective and competing drug-design constraints remains challenging. We propose C-Moral…

cs.CL2026

BeyondBench: Contamination-Resistant Evaluation of Reasoning in Language Models

Gaurav Srivastava, Aafiya Hussain, Zhenyu Bi +5

Evaluating language models fairly is increasingly difficult as static benchmarks risk contamination by training data, obscuring whether models truly reason or recall. We introduce…

cs.CV2026

InterPrior: Scaling Generative Control for Physics-Based Human-Object Interactions

Sirui Xu, Samuel Schulter, Morteza Ziyadi +4

Humans rarely plan whole-body interactions with objects at the level of explicit whole-body movements. High-level intentions, such as affordance, define the goal, while coordinated…

cs.MM2025

MAVERIX: Multimodal Audio-Visual Evaluation and Recognition IndeX

Liuyue Xie, Avik Kuthiala, George Z. Wei +12

We introduce MAVERIX (Multimodal audiovisual Evaluation and Recognition IndeX), a unified benchmark to probe the video understanding in multimodal LLMs, encompassing video, audio,…

cs.AI2025

JudgeBoard: Benchmarking and Enhancing Small Language Models for Reasoning Evaluation

Zhenyu Bi, Gaurav Srivastava, Yang Li +4

While small language models (SLMs) have shown promise on various reasoning tasks, their ability to judge the correctness of answers remains unclear compared to large language model…

cs.CV2025

VMDT: Decoding the Trustworthiness of Video Foundation Models

Yujin Potter, Zhun Wang, Nicholas Crispino +11

As foundation models become more sophisticated, ensuring their trustworthiness becomes increasingly critical; yet, unlike text and image, the video modality still lacks comprehensi…