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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…
The World Won't Stay Still: Programmable Evolution for Agent Benchmarks
Guangrui Li, Yaochen Xie, Yi Liu +11
LLM-powered tool-calling agents fulfill user requests by interacting with environments, querying data, and invoking tools in a multi-turn process. Yet, most existing benchmarks eva…
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…
Subspace Alignment for Vision-Language Model Test-time Adaptation
Zhichen Zeng, Wenxuan Bao, Xiao Lin +8
Vision-language models (VLMs), despite their extraordinary zero-shot capabilities, are vulnerable to distribution shifts. Test-time adaptation (TTA) emerges as a predominant strate…