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cs.AI2026
ZipRL: Adaptive Multi-Turn Context Compression with Hindsight Response Replay
Zhexin Hu, Li Wang, Xiaohan Wang +4
Adaptive context compression is vital for scaling Large Language Models (LLMs) to complex, multi-turn agent tasks. However, rule-based compression methods may discard task-critical…
cs.SD2026
VoiceGiraffe: A Benchmark for Extreme Long-Context Audio-Language Understanding
Jashin Ye, Dongxiao Wang, Yixuan Ye +10
While large audio language models (LALMs) have achieved remarkable progress in audio processing at the second- or minute-level scale, understanding hour-level audio remains a funda…
cs.LG2026
When Self-Belief Misleads: Active Label Acquisition for Reinforcement Learning with Verifiable Rewards
Li Wang, Xiaodong Lu, Xiaohan Wang +5
Large Language Models (LLMs) have achieved remarkable advancements in reasoning capabilities empowered by Reinforcement Learning with Verifiable Rewards (RLVR). Nonetheless, RLVR i…