collaborators

16 papers

cs.CL2026

Ripple-Pivot Search: Active Parallel Decoding for Diffusion Large Language Models

Yushi Ye, Xu Chen, Haoyun Jiang +7

Diffusion Large Language Models (dLLMs) have emerged as a competitive alternative to autoregressive language models, offering the potential for substantially faster inference throu…

cs.CV2026

LiteFrame: Efficient Vision Encoders Unlock Frame Scaling in Video LLMs

Jihwan Kim, Nikhil Parthasarathy, Danfeng Qin +5

The fundamental challenge in scaling Video Large Language Models (Video LLMs) to long-form video lies in managing the explosion of visual-token context length. Existing strategies…

cs.CL2026

Hidden Human-Like Nature of Machine-Generated Texts: Theory and Detection Enhancement

Chenwang Wu, Yiu-ming Cheung, Bo Han +1

Machine-generated texts (MGTs) produced by large language models (LLMs) are increasingly prevalent across various applications, while their potential misuse in fake news propagatio…

cs.AI2026

Conditional Equivalence of DPO and RLHF: Implicit Assumption, Failure Modes, and Provable Alignment

Zhiqin Yang, Yonggang Zhang, Wei Xue +3

Direct Preference Optimization (DPO) has emerged as a popular alternative to Reinforcement Learning from Human Feedback (RLHF), offering theoretical equivalence with simpler implem…

cs.NE2026

What Do Evolutionary Coding Agents Evolve?

Nico Pelleriti, Sree Harsha Nelaturu, Zhanke Zhou +4

Recent work pairs LLMs with evolutionary search to iteratively generate, modify, and select code using task-specific feedback. These systems have produced strong results in mathema…

cs.CL2026

Rethinking How to Remember: Beyond Atomic Facts in Lifelong LLM Agent Memory

Jingwei Sun, Jianing Zhu, Jiangchao Yao +2

To enable reliable long-term interaction, LLM agents require a memory system that can faithfully store, efficiently retrieve, and deeply reason over accumulated dialogue history. M…