collaborators

14 papers

cs.LG2026

RRPO: Reference-Relative Policy Optimization with Stratified Conditional Rollouts

Yuxin Xiong, Xunyi Jiang, Rohan Surana +8

Group Relative Policy Optimization (GRPO) has shown strong effectiveness in reinforcement learning from verifiable feedback, where sampled rollouts can be compared within a group u…

cs.AI2026

Can We Break LLMs Out of Self-Loops? Fine-Grained Reasoning Control with Activation Steering

Sheldon Yu, Tong Yu, Xunyi Jiang +6

Extended reasoning has become standard for frontier Large Language Models (LLMs), yet the trajectories these models produce remain largely uncontrollable. Existing methods for shap…

cs.LG2026

F-GRPO: Factorized Group-Relative Policy Optimization for Unified Candidate Generation and Ranking

Rohan Surana, Gagan Mundada, Junda Wu +9

Traditional retrieval pipelines optimize utility through stages of candidate retrieval and reranking, where ranking operates over a predefined candidate set. Large Language Models…

cs.LG2026

MASS-DPO: Multi-negative Active Sample Selection for Direct Policy Optimization

Rohan Surana, Xintong Li, Sheldon Yu +7

Multi-negative preference optimization under the Plackett--Luce (PL) model extends Direct Preference Optimization (DPO) by leveraging comparative signals across one preferred and m…

cs.LG2026

Skill-R1: Agent Skill Evolution via Reinforcement Learning

Yash Vishe, Rohan Surana, Xunyi Jiang +8

Agentic large language models often rely on skills, reusable natural language procedures that guide planning, action, and tool use. In practice, skills are typically improved throu…

cs.LG2026

Skill-CMIB: Multimodal Agent Skill for Consistent Action via Conditional Multimodal Information Bottleneck

Zihan Huang, Junda Wu, Tong Yu +6

While LLM-based agents excel at planning and executing long action sequences, their execution often remains inconsistent across trials, limiting reliability. Consolidating agent co…

cs.LG2026

Generate, Filter, Control, Replay: A Comprehensive Survey of Rollout Strategies for LLM Reinforcement Learning

Rohan Surana, Gagan Mundada, Xunyi Jiang +19

Reinforcement learning (RL) has become a central post-training tool for improving the reasoning abilities of large language models (LLMs). In these systems, the rollout, the trajec…

cs.LG2026

WS-GRPO: Weakly-Supervised Group-Relative Policy Optimization for Rollout-Efficient Reasoning

Gagan Mundada, Zihan Huang, Rohan Surana +8

Group Relative Policy Optimization (GRPO) is effective for training language models on complex reasoning. However, since the objective is defined relative to a group of sampled tra…

cs.LG2026

AMPS: Adaptive Modality Preference Steering via Functional Entropy

Zihan Huang, Xintong Li, Rohan Surana +5

Multimodal Large Language Models (MLLMs) often exhibit significant modality preference, which is a tendency to favor one modality over another. Depending on the input, they may ove…

cs.IR2026

Evaluation on Entity Matching in Recommender Systems

Zihan Huang, Rohan Surana, Zhouhang Xie +3

Entity matching is a crucial component in various recommender systems, including conversational recommender systems (CRS) and knowledge-based recommender systems. However, the lack…

cs.CV2025

Importance Sampling for Multi-Negative Multimodal Direct Preference Optimization

Xintong Li, Chuhan Wang, Junda Wu +4

Direct Preference Optimization (DPO) has recently been extended from text-only models to vision-language models. However, existing methods rely on oversimplified pairwise compariso…

cs.SD2025

MusiCRS: Benchmarking Audio-Centric Conversational Recommendation

Rohan Surana, Amit Namburi, Gagan Mundada +4

Conversational recommendation has advanced rapidly with large language models (LLMs), yet music remains a uniquely challenging domain in which effective recommendations require rea…

cs.LG2025

In-context Ranking Preference Optimization

Junda Wu, Rohan Surana, Zhouhang Xie +6

Recent developments in Direct Preference Optimization (DPO) allow large language models (LLMs) to function as implicit ranking models by maximizing the margin between preferred and…

cond-mat.str-el2025

Interacting Chern insulator transition on the sphere: revealing the Gross-Neveu-Yukawa criticality

Zhi-Qiang Gao, Taige Wang, Dung-Hai Lee

In two spatial dimensions, the transition between topological and trivial Chern insulators exemplifies a class of beyond-Landau critical phenomena. We show that the interaction-dri…