most citedFast on the Easy, Deep on the Hard: Efficient Reasoning via Powered Length Penalty

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.AI2025

Adaptive Reasoning Executor: A Collaborative Agent System for Efficient Reasoning

Zehui Ling, Deshu Chen, Yichi Zhang +4

Recent advances in Large Language Models (LLMs) demonstrate that chain-of-thought prompting and deep reasoning substantially enhance performance on complex tasks, and multi-agent s…

cs.LG2025

Unleashing Flow Policies with Distributional Critics

Deshu Chen, Yuchen Liu, Zhijian Zhou +2

Flow-based policies have recently emerged as a powerful tool in offline and offline-to-online reinforcement learning, capable of modeling the complex, multimodal behaviors found in…

cs.CV2025

Minimal Semantic Sufficiency Meets Unsupervised Domain Generalization

Tan Pan, Kaiyu Guo, Dongli Xu +8

The generalization ability of deep learning has been extensively studied in supervised settings, yet it remains less explored in unsupervised scenarios. Recently, the Unsupervised…

eess.IV2025

PET2Rep: Towards Vision-Language Model-Drived Automated Radiology Report Generation for Positron Emission Tomography

Yichi Zhang, Wenbo Zhang, Zehui Ling +12

Positron emission tomography (PET) is a cornerstone of modern oncologic and neurologic imaging, distinguished by its unique ability to illuminate dynamic metabolic processes that t…

cs.CL20251 cited

Fast on the Easy, Deep on the Hard: Efficient Reasoning via Powered Length Penalty

Zehui Ling, Deshu Chen, Hongwei Zhang +3

Large language models (LLMs) have demonstrated significant advancements in reasoning capabilities, performing well on various challenging benchmarks. Techniques like Chain-of-Thoug…