activity
20242026
collaborators

14 papers

cs.CV2026

VOTE: Vision-Language-Action Optimization with Trajectory Ensemble Voting

Juyi Lin, Amir Taherin, Arash Akbari +11

Recent large-scale Vision Language Action (VLA) models have shown superior performance in robotic manipulation tasks guided by natural language. However, current VLA models suffer…

cs.LG2026

Token Reduction Should Go Beyond Efficiency in Generative Models -- From Vision, Language to Multimodality

Zhenglun Kong, Yize Li, Fanhu Zeng +7

In Transformer architectures, tokens\textemdash discrete units derived from raw data\textemdash are formed by segmenting inputs into fixed-length chunks. Each token is then mapped…

cs.RO2026

When Should a Robot Think? Resource-Aware Reasoning via Reinforcement Learning for Embodied Robotic Decision-Making

Jun Liu, Pu Zhao, Zhenglun Kong +12

Embodied robotic systems increasingly rely on large language model (LLM)-based agents to support high-level reasoning, planning, and decision-making during interactions with the en…

cs.LG2026

Structured Agent Distillation for Large Language Model

Jun Liu, Zhenglun Kong, Peiyan Dong +10

Large language models (LLMs) exhibit strong capabilities as decision-making agents by interleaving reasoning and actions, as seen in ReAct-style frameworks. Yet, their practical de…

eess.AS2026

A Survey of Advancing Audio Super-Resolution and Bandwidth Extension from Discriminative to Generative Models

Ningyuan Yang, Yize Li, Diego A. Cuji +4

Audio super-resolution (SR), also referred to as bandwidth extension (BWE), aims to reconstruct high-fidelity signals from low-resolution (LR) or band-limited (BL) observations, an…

cs.CL2026

Toward Adaptive Large Language Models Structured Pruning via Hybrid-grained Weight Importance Assessment

Jun Liu, Zhenglun Kong, Pu Zhao +9

Structured pruning for large language models (LLMs) has garnered significant academic interest due to its ability to efficiently compress and accelerate LLMs by eliminating redunda…