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cs.CL2026
ATTS: Asynchronous Test-Time Scaling via Conformal Prediction
Jing Xiong, Qiujiang Chen, Fanghua Ye +11
Large language models (LLMs) benefit from test-time scaling but are often hampered by high inference latency. Speculative decoding is a natural way to accelerate the scaling proces…
cs.CL2026
OVD: On-policy Verbal Distillation
Jing Xiong, Hui Shen, Shansan Gong +7
Knowledge distillation offers a promising path to transfer reasoning capabilities from large teacher models to efficient student models; however, existing token-level on-policy dis…
cs.CL2025
DeepDiver: Adaptive Search Intensity Scaling via Open-Web Reinforcement Learning
Wenxuan Shi, Haochen Tan, Chuqiao Kuang +7
Information seeking demands iterative evidence gathering and reflective reasoning, yet large language models (LLMs) still struggle with it in open-web question answering. Existing…