activity
20242026
most citedMoveLight: Enhancing Traffic Signal Control through Movement-Centric Deep Reinforcement Learning

2 citations · 2 across the 14 of their papers we have counts for

collaborators

14 papers

cs.AI2026

Buried in Textual Debt: Context Pruning with Visual Evidence Preservation for MLLM Agents

Yuchen Huang, Sijia Li, Jun Zhang +1

Multimodal Large Language Models (MLLMs) are increasingly deployed as multi-step agents, where explicit reasoning supports task decomposition and tool coordination but also accumul…

cs.RO2026

PACE: Adaptive Budget Allocation for Time-Efficient Embodied Planning

Yuchen Huang, Xijiang Ying, Zhenhua Ma +14

Reasoning-enhanced large language models have achieved remarkable improvements in planning tasks, yet their deployment in embodied systems remains impractical due to prohibitive in…

cs.AI2026

CDR-Bench: Evaluating Faithful Execution of Compositional, Order-Sensitive Data Refinement Recipes

Yuchen Huang, Xiang Li, Zhenqing Ling +5

Data refinement involves executing multi-step recipes over evolving text states, where both composition and execution order of processing operators determine the outcome. While exi…

cs.LG2026

GEAR: Granularity-Adaptive Advantage Reweighting for LLM Agents via Self-Distillation

Sijia Li, Yuchen Huang, Zifan Liu +7

Reinforcement learning has become a widely used post-training approach for LLM agents, where training commonly relies on outcome-level rewards that provide only coarse supervision.…

cs.MM2026

2D or 3D: Who Governs Salience in VLA Models? -- Tri-Stage Token Pruning Framework with Modality Salience Awareness

Zihao Zheng, Sicheng Tian, Zhihao Mao +8

Vision-Language-Action (VLA) models have emerged as the mainstream of embodied intelligence. Recent VLA models have expanded their input modalities from 2D-only to 2D+3D paradigms,…

cs.LG2025

Environment Scaling for Interactive Agentic Experience Collection: A Survey

Yuchen Huang, Sijia Li, Minghao Liu +5

LLM-based agents can autonomously accomplish complex tasks across various domains. However, to further cultivate capabilities such as adaptive behavior and long-term decision-makin…