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…Experiments on LLMs and VLMs demonstrate LenVM provides a highly effective signal at inference time. On the LIFEBench exact length matching task, applying LenVM to a 7B model improves the length score…
…Second, reward and credit signals attach to eight credit- or signal-bearing units from token to team; explicit counterfactual message-level credit remains especially sparse in our curated pool. Third, orchestration learning…
…Existing detection methods primarily rely on output-level signals such as likelihood or entropy, which become unreliable for RL-trained models since RL shapes behavior through trajectory-level rewards rather than token…
…Ishpuneet Singh , , Uday Pratap Singh Atwal , , , Abstract BEACON is a large-scale multimodal dataset capturing diverse behavioral signals during competitive gaming to advance continuous authentication and behavioral biometrics research. AI-generated summary…
…Used as a streaming signal , they support a more efficient form of test-time scaling : pruning low-scoring candidates mid-generation reduces generated tokens by over 50\% while preserving the Findings quality…
…DRPO preserves the same trust-region geometry as DPPO while inducing bounded, continuous gradient weights that attenuate diverging updates and provide corrective signals beyond the boundary. Experiments across model scales, architectures, and…
…In TRL-CTbench , generic text encoders often lead on tasks with strong surface-text signal, while tabular specialists win where their pretraining objective aligns with the task. In TRL-Rbench , within-table…
…Tong Zheng , , , , , , Runpeng Dai , , , Tianyi Xiong , , , Abstract AutoTTS automates test-time scaling strategy discovery by formulating it as controller synthesis over reasoning trajectories and probe signals, achieving improved accuracy-cost tradeoffs with…
…Fusing multi-timescale signals in RL can trigger optimization pathologies. We identify two specific failure modes in Actor-Critic architectures: Surrogate Objective Hacking (policy gradients exploiting dynamic routing weights) and the Paradox…
…Yunho Choi , Jongwon Lim , , , , Abstract POISE enables stable and efficient policy optimization for large reasoning models by estimating baselines using internal model signals, reducing computational overhead while maintaining performance comparable to existing…