30 citations · 33 across the 10 of their papers we have counts for
5 papers · 1 filter
LLM Agents for Automated Post-Training via Structured Recipe Optimization
Ruohong Liu, Bohan Tang, Lekang Jiang +2
Automated post-training transforms pre-trained large language models (LLMs) into models capable of handling diverse domains by automatically constructing and optimizing a recipe of…
Recursive Harness Self-Improvement for Frontier Reasoning Data Synthesis
Wenlong Zhang, Zhengbo Jiao, Chenxu Zhang +5
Generating progressively harder reasoning problems requires synthesis procedures that adapt as the task distribution evolves. Existing task-level recursion reuses generated problem…
Benchmarking Patent Drafting from Inventor-Style Disclosures
Lekang Jiang, Wenjun Sun, Stephan Goetz
While recent large language models (LLMs) have achieved promising results on individual patent drafting tasks, they fundamentally fail to investigate the core challenge of real-wor…
ADIAS: Automated Design of Interactive Agentic Systems
Lekang Jiang, Bohan Tang, Stephan Goetz +1
Self-evolving agents can improve without updating model weights by iteratively optimizing the harness based on evaluation feedback. Existing methods are largely candidate-centric:…
When Reasoning Hurts Legal Drafting: The Verbalization Bottleneck in Patent Claim Generation
Lekang Jiang, Wenjun Sun, Stephan Goetz
Patent claim drafting is a challenging legal drafting task that requires technical expertise, precise linguistic control, strict adherence to formal conventions, and the preservati…