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cs.CL2026
Learning from Supervision with Semantic and Episodic Memory: A Reflective Approach to Agent Adaptation
Jackson Hassell, Dan Zhang, Hannah Kim +2
We investigate how agents built on pretrained large language models (LLMs) can learn target classification functions from labeled examples without parameter updates. While conventi…
cs.CL2026★ 1 cited
Towards Reliable Benchmarking: A Contamination Free, Controllable Evaluation Framework for Multi-step LLM Function Calling
Seiji Maekawa, Jackson Hassell, Pouya Pezeshkpour +2
Existing benchmarks for tool-augmented language models (TaLMs) lack fine-grained control over task difficulty and remain vulnerable to data contamination. We present FuncBenchGen,…