6 papers
FreeEvolve: Learning to Evolve Beyond Fixed Loops
Lecheng Kong, Like Hui, Nikos Kanakaris +3
Agent evolvers automate the design of the prompts, skills and workflows around language model agents, yet the optimization process they follow is still designed by hand: a fixed se…
MILO: Automated Harness Discovery via Orchestrated Multi-Agent Evolution
Prithwish Jana, Mononito Goswami, Hao Liu +9
Modern agentic systems combine an AI model with a harness that controls execution and environmental interactions. Harness design strongly affects long-horizon performance, yet its…
A Pinch of SFT, A Dash of RL: When Reinforcement Learning Helps Long-Horizon Advertising Agents
Aakash Kolekar, Sahika Genc, Bunyamin Sisman +6
Enterprise analytics agents solve long-horizon tool-use problems over distributed business data, requiring retrieval, reasoning, API calls, code execution, and adaptation to interm…
CRAFT: Learn the Schema, Execute the Plan
Aakash Kolekar, Sahika Genc, Shahriar Shariat +10
Enterprise coding agents translate natural-language analytical requests into executable code over proprietary APIs, schemas, and metric definitions. Yet the prevailing deployment p…
An Efficient Plugin Method for Metric Optimization of Black-Box Models
Siddartha Devic, Nurendra Choudhary, Anirudh Srinivasan +3
Many machine learning algorithms and classifiers are available only via API queries as a ``black-box'' -- that is, the downstream user has no ability to change, re-train, or fine-t…
GT2Vec: Large Language Models as Multi-Modal Encoders for Text and Graph-Structured Data
Jiacheng Lin, Kun Qian, Haoyu Han +9
Graph-structured information offers rich contextual information that can enhance language models by providing structured relationships and hierarchies, leading to more expressive e…