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From the 1 of 8 linked papers with an AI index.

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8 papers

cs.CV2026

Beyond Chain-of-Thought: Rewrite as a Universal Interface for Generative Multimodal Embeddings

Peixi Wu, Ke Mei, Feipeng Ma +15

The paper introduces RIME, a rewrite-driven framework that improves multimodal embeddings by jointly optimizing generation and retrieval-friendly rewriting, aligning generative and…

cs.LG2026

From Generic Correlation to Input-Specific Credit in On-Policy Self Distillation

Guobin Shen, Lei Huang, Xiang Cheng +4

On-policy self-distillation has emerged as a promising paradigm for post-training language models, in which the model conditions on environment feedback to serve as its own teacher…

cs.LG2026

Anti-Self-Distillation for Reasoning RL via Pointwise Mutual Information

Guobin Shen, Xiang Cheng, Chenxiao Zhao +4

On-policy self-distillation, where a student is pulled toward a copy of itself conditioned on privileged context (e.g., a verified solution or feedback), offers a promising directi…

cs.LG2026

VESPO: Variational Sequence-Level Soft Policy Optimization for Stable Off-Policy LLM Training

Guobin Shen, Chenxiao Zhao, Xiang Cheng +2

Off-policy updates are inevitable in reinforcement learning (RL) for large language models (LLMs) due to rollout staleness from asynchronous training and mismatches between trainin…

cs.CV2026

DeepEyesV2: Toward Agentic Multimodal Model

Jack Hong, Chenxiao Zhao, ChengLin Zhu +3

Agentic multimodal models should not only comprehend text and images, but also actively invoke external tools, such as code execution environments and web search, and integrate the…

cs.CL2026

Bootstrapping Exploration with Group-Level Natural Language Feedback in Reinforcement Learning

Lei Huang, Xiang Cheng, Chenxiao Zhao +6

Large language models (LLMs) typically receive diverse natural language (NL) feedback through interaction with the environment. However, current reinforcement learning (RL) algorit…