Tracked topic
…We address this with a two-stage evaluation pipeline that pairs structured per-sample scoring across five edit-centric criteria with a grid-based calibration step in which the VLM re-scores…
…Structured Judge Rewards for Generalizable Reasoning (2026) Calibrating LLMs with Semantic-level Reward (2026) Beyond Reasoning: Reinforcement Learning Unlocks Parametric Knowledge in LLMs (2026) Step-wise Rubric Rewards for LLM Reasoning (2026…
…Target-Aligned Parallel Draft Model for Dual-Mode Speculative Decoding (2026) Calibrated Speculative Decoding: Frequency-Guided Candidate Selection for Efficient Inference (2026) D-PACE: Dynamic Position-Aware Cross-Entropy for Parallel Speculative…
…To close this gap, we recommend calibrated confidence , evidence-grounded explanations , and mechanisms that help users refine trust . View arXiv page View PDF Add to collection Community AI systems are fallible, and…
…head-wise retention follows a two-level structural regularity -- an input-invariant head ranking with narrowly bounded per-head ratios -- that can be calibrated offline from as few as 50 samples. Building…
…An entropy-adaptive scaling mechanism modulates the n-gram contribution based on the SSM 's predictive confidence, preventing over-correction when the neural model is already well-calibrated. On the standard enwik8…
…In the slow loop, outcome-calibrated memory attribution and privileged hindsight distill these four abilities into the deployable policy. Across multi-domain benchmarks, OPD-Evolver surpasses memory systems such as ReasoningBank by…
…We also release Claw- SWE-Bench Lite for faster validation, which is an 80-instance subset selected by a cost-aware, rank-aware procedure over 17 calibration columns. On the full benchmark…
…Overall, these findings suggest that multilingual parallel-data assessment is best approached as a direction-aware routing and calibration problem, where no single universal metric is expected to suffice across all languages…
…The framework is intended as a controlled testbed, useful as a calibration environment for geometric estimators and a sandbox for probing theoretical assumptions. To illustrate its use, we present two application studies…