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cs.CL2026
Prune as You Generate: Online Rollout Pruning for Faster and Better RLVR
Haobo Xu, Sirui Chen, Ruizhong Qiu +5
Reinforcement Learning with Verifiable Rewards (RLVR) has significantly advanced the reasoning capabilities of Large Language Models (LLMs). However, methods such as GRPO and DAPO…
cs.CL2026
Attn-GS: Attention-Guided Context Compression for Efficient Personalized LLMs
Shenglai Zeng, Tianqi Zheng, Chuan Tian +10
Personalizing large language models (LLMs) to individual users requires incorporating extensive interaction histories and profiles, but input token constraints make this impractica…