works on

From the 2 of 20 linked papers with an AI index.

activity
20242026
collaborators

19 papers

cs.CV2026

Self-Evolving Code-with-Image Reasoning

Tianze Yang, Liang Wu, Ruitong Sun +6

Multimodal models increasingly reach for tools when solving visual tasks (crop, zoom, rotate, brighten), a paradigm known as thinking-with-images. The central challenge is one of p…

cs.AI2026

Recursive Synthesis for Long-Horizon Terminal Tasks

Zhongzhi Li, Yucheng Shi, Zongxia Li +8

High-quality long-horizon training data for terminal agents is expensive to produce, often costing hundreds to thousands of dollars per task, because each task must keep the instru…

cs.LG2026

Stale but Stable: Staleness-Adaptive Trust Regions for Stabilizing Asynchronous Reinforcement Learning

Junyao Yang, Yucheng Shi, Zongxia Li +6

Asynchronous reinforcement learning improves throughput by decoupling rollout generation from optimization, but the resulting staleness is an inevitable byproduct, compounded joint…

cs.AI2026

Harness Handbook: Making Evolving Agent Harnesses Readable,Navigable, and Editable

Ruhan Wang, Yucheng Shi, Zongxia Li +7

The paper presents the Harness Handbook, a tool that automatically creates a behavior‑centric view of AI agent harness code using static analysis and LLM assistance, enabling devel…

cs.AI2026

Long-Horizon-Terminal-Bench: Testing the Limits of Agents on Long-Horizon Terminal Tasks with Dense Reward-Based Grading

Zongxia Li, Zhongzhi Li, Yucheng Shi +10

The paper presents Long-Horizon-Terminal-Bench, a benchmark of 46 extended tasks with fine-grained intermediate rewards to evaluate AI agents' long-horizon planning and debugging a…

cs.PF2026

Cluster, Route, Escalate: Cascaded Framework for Cost-Aware LLM Serving

Yasmin Moslem, Magdalena Kacmajor, Vasudevan Nedumpozhimana +11

Efficient deployment of large language models (LLMs) in production forces a trade-off between accuracy and cost. Operators often default to a single model that is either expensive…