5 papers
Hint Tuning: Less Data Makes Better Reasoners
Siqi Fan, Minghao Li, Xiaoqian Ma +6
Large reasoning models achieve high accuracy through extended chain-of-thought but generate 5--8 more tokens than necessary, applying verbose reasoning uniformly regardless of prob…
Geometry Guided Self-Consistency for Physical AI
Yinwei Dai, Zhuofu Chen, Lijie Yang +1
State-of-the-art physical AI models generate a chunk of actions per inference through diffusion or flow matching, iteratively refining an initial noise sample into an action trajec…
Slipstream: Trajectory-Grounded Compaction Validation for Long-Horizon Agents
Zhuofu Chen, Rui Pan, Yinwei Dai +1
To cope with the large contexts that long-horizon LLM agents produce, modern frameworks increasingly rely on compaction -- invoking an LLM to rewrite the accumulated trajectory int…
Fail Fast, Win Big: Rethinking the Drafting Strategy in Speculative Decoding via Diffusion LLMs
Rui Pan, Zhuofu Chen, Hongyi Liu +2
Diffusion Large Language Models (dLLMs) offer fast, parallel token generation, but their standalone use is plagued by an inherent efficiency-quality tradeoff. We show that, if care…
Aragog: Just-in-Time Model Routing for Scalable Serving of Agentic Workflows
Yinwei Dai, Zhuofu Chen, Anand Iyer +1
Agentic workflows have emerged as a powerful paradigm for solving complex, multi-stage tasks, but serving them at scale is computationally expensive given the many LLM inferences t…