6 papers · 1 filter
Selecting Diverse SFT Traces Improves Post-RL Generalization
Dylan Zhang, Mingyuan Wu, Jinning Li
Verified solutions are not equally useful for preparing reasoning models for reinforcement learning (RL). We present a comprehensive study of route diversity, the variation in the…
SLIDEFORGE: An LLM Agent for Controllable Editing of Slides as Structured Artifacts
Haozhen Zheng, Fulin Wang, Tianhu Xiong +6
Current AI agents compellingly describe slides. However, AI-assisted slide editing requires more than understanding: the output must retain layout, style, component structure, and…
SVR-R1: Bootstrapping Multi-modal Reasoning with Self-verification in Reinforcement Learning
Mingyuan Wu, Jingcheng Yang, Shengyi Qian +11
We introduce Self-Verified Reasoner (SVR-R1), a multi-turn RL framework that turns a model's own verification into a learning signal for multimodal reasoning. For each query, the m…
Spreadsheet-RL: Advancing Large Language Model Agents on Realistic Spreadsheet Tasks via Reinforcement Learning
Banghao Chi, Yining Xie, Mingyuan Wu +9
Spreadsheet systems (e.g., Microsoft Excel, Google Sheets) play a central role in modern data-centric workflows. As AI agents grow increasingly capable of automating complex tasks,…
QoS-QoE Translation with Large Language Model
Yingjie Yu, Mingyuan Wu, Ahmadreza Eslaminia +3
QoS-QoE translation is a fundamental problem in multimedia systems because it characterizes how measurable system and network conditions affect user-perceived experience. Although…
Circuit Tracing in Vision-Language Models: Understanding the Internal Mechanisms of Multimodal Thinking
Jingcheng Yang, Tianhu Xiong, Shengyi Qian +2
Vision-language models (VLMs) are powerful but remain opaque black boxes. We introduce the first framework for transparent circuit tracing in VLMs to systematically analyze multimo…