94 citations · 276 across the 21 of their papers we have counts for
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cs.AI2026
Know What You Don't Know: Agentic Data Synthesis by Evolving Generation Space for Closed-Loop Learning
Wei Yang, Qing Ping, Youzhi Luo +4
The continued improvement of large language models increasingly depends on synthetic experience, yet effective data synthesis for interactive agents requires not only executable an…
cs.CV2026
StructRL: Online Structured Reinforcement Learning for Long-Horizon Vision-Language-Action Tasks
Ziyi Yin, Sangmin Woo, Kang Zhou +4
Vision-language-action (VLA) models perform well on shorter-horizon manipulation tasks but still struggle with long-horizon tasks that require multiple dependent manipulations from…
cs.LG2026
SWE-Proof: Can Language Models Resolve Real-World Issues with Machine-Checked Proofs?
George Ma, Benjamin Mikek, Haoyu Li +9
Ensuring the correctness of LLM-generated code is a core challenge for modern software engineering. Benchmarks for agentic code generation check correctness with held-out test suit…