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cs.CL2025
Can Compact Language Models Search Like Agents? Distillation-Guided Policy Optimization for Preserving Agentic RAG Capabilities
Rikuto Kotoge, Mai Nishimura, Jiaxin Ma
Reinforcement Learning has emerged as a dominant post-training approach to elicit agentic RAG behaviors such as search and planning from language models. Despite its success with l…
cs.IR2025
PLASMA: A Layout-Aware Benchmark Reveals Memory Layout Matters for Graph-based ANNS on GPU
Yutaro Oguri, Mai Nishimura, Yusuke Matsui
We propose a latform for ayout-ware earch and emory rrangement (), a unified evaluation fra…