… We conclude that representational accuracy is distinct from recall and that human-AI alignment is dependent on how accurately the user is represented. Representational accuracy makes that alignment testable. …
Papers arxiv:2605.29648 Verifiable Rewards Beyond Math and Code: Lightweight Corpus-Grounded Process Supervision for Factual Question Answering Published on May 28 Submitted by Dehai Min on May 29 University of Illinois Chicago Authors: Shicheng Fan , Haochang Hao , , , , Abstract CorVer, a corpus-… …
… Zhao on Jun 2 Authors: , Hui Chen , , Abstract FineVerify is a self-verification framework for agentic search that improves accuracy through decomposed sub-question checking and trajectory selection. …
… DeltaRubric operates in two steps: acting first as a Disagreement Planner, the model generates a neutral, instance-specific verification checklist. Transitioning into a Checklist Verifier, it executes these self-generated checks against the image and question to produce the final grounded judgment. …
… Across two Qwen3 architectures/scales MoE Qwen3-30B-A3B, dense Qwen3-4B and both in-domain AIME25 and out-of-domain GPQA-Diamond benchmarks, SxS improves accuracy--content-latency Pareto trade-offs under token-level proxies such as inter-update waiting. …
… Through comprehensive evaluations of state-of-the-art VLMs, we identify stress-specific failure modes and reveal that different physical factors degrade different embodied capabilities, which are often obscured by aggregate accuracy. …
… Across five benchmarks spanning math AIME'25 , abstract reasoning ARC-AGI-1 , graduate-level science GPQA , code generation MBPP , and logic puzzles Sudoku , SePO consistently outperforms Manual-CoT, TextGrad, and MetaSPO, improving the average accuracy by 4.49 points compared to Manual-CoT. …
… Under sustained adversarial pressure we find a previously undocumented failure mode: the chain-of-thought stays factually correct from first turn to last while the emitted answer flips wrong. …
… Removing deterministic checks drops accuracy to 17.91%, showing that the symbolic environment performs the verification step that the model cannot reliably replace. …
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