collaborators

8 papers

cs.LG2026

Dynamic Harness Search: Building Multi-Agent Systems Per-Query via Prediction

Som Sagar, Shasha Li, Hejie Cui +2

Agent harnesses specify the roles, instructions, tools, and communication structure used to solve a task, and the right harness depends on the query. Because the value of each desi…

cs.IR2026

RPTune: Learned Context Curation for LLM Catalog Search

Chuxuan Hu, Hejie Cui, Norman Huang +3

For small merchant businesses (SMBs) whose catalogs fit within a long-context LLM, full-catalog prompting offers a compelling alternative to multi-stage retrieval designed primaril…

cs.AI2026

AdviSD: Learning to Advise Frontier LLMs via Targeted Multi-Turn Self-Distillation

Rishabh Agrawal, Hejie Cui, Shasha Li +2

A small trainable advisor can steer a frozen language-model executor using natural-language advice. In addition to learning from task rewards, the advisor can use feedback from com…

cs.CL2026

Customer-Agent: Overcoming Context Limitations in Ultra-Long Shopping Trajectories via Tool-Augmented Agents and RLVR

Hongye Liu, Rongmei Lin, Anurag Kashyap +4

Understanding customer shopping trajectories is essential for enabling personalized shopping experiences. However, shopping records (i.e., customer's search, clicks, purchases, etc…

cs.AI2026

TPO: Uncertainty-Guided Exploration Control for Stable Multi-Turn Agentic Reinforcement Learning

Haixin Wang, Hejie Cui, Chenwei Zhang +7

Recent progress in multi-turn reinforcement learning (RL) has significantly improved reasoning LLMs' performances on complex interactive tasks. Despite advances in stabilization te…

cs.CL2026

Stepwise Penalization for Length-Efficient Chain-of-Thought Reasoning

Xintong Li, Sha Li, Rongmei Lin +10

Large reasoning models improve with more test-time computation, but often overthink, producing unnecessarily long chains-of-thought that raise cost without improving accuracy. Prio…

cs.LG2026

HeaPA: Difficulty-Aware Heap Sampling and On-Policy Query Augmentation for LLM Reinforcement Learning

Weiqi Wang, Xin Liu, Binxuan Huang +13

RLVR has become a standard recipe for training LLMs on reasoning tasks with verifiable outcomes, but when rollout generation dominates the cost, efficiency hinges on which prompts…

cs.AI2025

WebCoach: Self-Evolving Web Agents with Cross-Session Memory Guidance

Genglin Liu, Shijie Geng, Sha Li +4

Multimodal LLM-powered agents have recently demonstrated impressive capabilities in web navigation, enabling agents to complete complex browsing tasks across diverse domains. Howev…