collaborators

10 papers

cs.CL2026

RING: Retrieval-Internalized Generation for Continual Large-Scale Knowledge Injection

Shicheng Xu, Liang Pang, Liyi Chen +7

Retrieval-augmented generation (RAG) improves factuality but adds latency and engineering overhead at serving time. We propose RING (Retrieval-Internalized Generation), a holistic…

cs.CV2026

EditCaption: Human-Refined SFT and HAE-DPO for Image Editing Instruction Synthesis

Xiangyuan Wang, Honghao Cai, Yunhao Bai +9

High-quality source-target image pairs with precise editing instructions are essential for instruction-guided image editing, yet constructing such training triplets at scale remain…

cs.AI2026

Anti-Length Shift: Dynamic Outlier Truncation for Training Efficient Reasoning Models

Wei Wu, Liyi Chen, Congxi Xiao +7

Large reasoning models enhanced by reinforcement learning with verifiable rewards have achieved significant performance gains by extending their chain-of-thought. However, this par…

cs.AI2026

Knowledge-Graph Paths as Intermediate Supervision for Self-Evolving Search Agents

Huyu Wu, Jun Liu, Xiaochi Wei +3

Self-evolving search agents reduce reliance on human-written training questions by generating and solving their own search tasks. We build on Search Self-Play (SSP), a representati…

cs.CV2026

MUSE: Resolving Manifold Misalignment in Visual Tokenization via Topological Orthogonality

Panqi Yang, Haodong Jing, Jiahao Chao +5

Unified visual tokenization faces a fundamental trade-off between high-fidelity pixel reconstruction (spatial equivariance) and semantic abstraction (conceptual invariance). We att…

cs.AI2026

SPARD: Self-Paced Curriculum for RL Alignment via Integrating Reward Dynamics and Data Utility

Xuyang Zhi, Peilun zhou, Chengqiang Lu +10

The evolution of Large Language Models (LLMs) is shifting the focus from single, verifiable tasks toward complex, open-ended real-world scenarios, imposing significant challenges o…