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cs.CL2026
Can David Beat Goliath? On Multi-Hop Reasoning with Resource-Constrained Agents
Hojae Han, Heeyun Jung, Jongyoon Kim +1
Multi-turn reasoning agents solve complex questions by decomposing them into intermediate retrieval or tool-use steps, for accumulating supporting evidence across turns. Meanwhile,…
cs.CL2026
Benchmarking Testing in Automated Theorem Proving
Jongyoon Kim, Hojae Han, Seung-won Hwang
Recent advances in large language models (LLMs) have shown promise in formal theorem proving, yet evaluating semantic correctness remains challenging. Existing evaluations rely on…
cs.CL2024
Arctic-SnowCoder: Demystifying High-Quality Data in Code Pretraining
Yuxiang Wei, Hojae Han, Rajhans Samdani
Recent studies have been increasingly demonstrating that high-quality data is crucial for effective pretraining of language models. However, the precise definition of "high-quality…