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cs.AI2026
Learning to Prove, Not Just to Answer: Reinforcement Learning from Formal Verification for Natural-Language Logical Reasoning
Qili Zhang, Qianren Mao, Hanze Cai +11
Large language models (LLMs) are increasingly deployed for natural-language logical reasoning, where the final answer is easy to check but the proof behind it is not. In natural-la…
cs.CL2026
Index SLM Technical Report
Tianjiao Li, Lusheng Zhang, Shien He +11
We present Index-1.9B, a series of open small language models developed at Bilibili. The series comprises four models: Index-1.9B-Base, a foundation model with 1.9 billion non-embe…
cs.LG2026
When Does Deep RL Beat Calibrated Baselines? A Benchmark Study on Adaptive Resource Control
Guilin Zhang, Chuanyi Sun, Kai Zhao +3
A properly calibrated rule-based autoscaler can beat every one of six mainstream deep reinforcement learning (DRL) algorithms on cost across every workload we test - so when, if ev…