Nune Ayvazan, Anthony Pym, Yu Hao · Oct 6, 2026 · Citations: 0
Critique EditMultilingual
Human revision is still required, not only to detect errors but also because of the ethical need for someone to take responsibility for any errors or delays in such messaging.
Muhammad Faraz Shoaib, Muhammad Qasim, Raisulhaq Mohammed Rizwan, Rahmatullah Safdar, Muzammil Adnan Shaik, Abdul Aleem Mohammed · Oct 6, 2026 · Citations: 0
Critique EditAutomatic MetricsGeneral
We present LOGIC, a controlled benchmark and evaluation framework in which locally deployable language models ground a request in a deterministic candidate-change inventory before selected changes are propagated through a typed electrical…
We introduce Video-RSI, a framework for recursive self-improvement in which a video understanding agent uses its own language model to revise its harness.
Across our evaluation settings on video understanding benchmarks, the evolved agent improves accuracy while processing fewer frames and achieves competitive accuracy-efficiency trade-offs against existing video understanding agents.
On the LACUNA localization-precision benchmark, our mean terminal utility is higher in all six negative preference optimization (NPO) and SimNPO comparisons: NPO margins range from +0.431 to +0.848, and SimNPO margins range from +0.503 to…
Relative to Static-IV, the primary four-field GradDiff evaluation has six wins, six ties, and no losses, with mean and median paired gains of +0.165 and +0.0025.
Extensive experiments across OCRBench v2.1, CC-OCR, in-house KIE Benchmark, OmniDocBench v1.6 and MDPBench demonstrate that PolyOCR achieves state-of-the-art or highly competitive performance.
Jiajun Wu, Jian Yang, Yaxin Du, Wei Zhang, Haowen Wang, Junhang Cheng · Aug 31, 2026 · Citations: 0
Critique EditSimulation EnvLawCoding
VLM-driven self-improvement of web code has a structural flaw: the model that proposes the repair is the model that judges it, and visual plausibility under that judge is a poor proxy for whether the page actually works.
Jinyoung Kim, Muhammad Khalifa, Lajanugen Logeswaran, Jaekyeom Kim, Moontae Lee, Honglak Lee · Aug 31, 2026 · Citations: 0
Pairwise PreferenceCritique EditGeneral
We use this reward to train an actor-tailored critic with GRPO, and use critique-guided refinements to construct DPO preference pairs for the actor, forming a co-evolving critic-actor loop where the critic adapts to the actor's changing…
To bridge this gap, we present MTPaperBananaBench, a benchmark for multi-turn diagram generation containing 292 images annotated with 3,518 user requirements.
To address these issues, we introduce PaperBanana-Interact, a multi-agent system that refines diagrams via an internal critique-and-refine loop.
Ante Kapetanovic, Kemal Altwlkany, Andro Mercep, Tomislav Duricic, Emanuel Lacic · Aug 26, 2026 · Citations: 0
Critique EditLlm As JudgeAutomatic MetricsGeneral
Across 192,000 attempted evaluations (185,271 successful), seven out of the eight evaluated models have 95% task-stratified bootstrap intervals below zero for the total anchored-metadata effect on 20 fixed texts.
On categorical industry data with human-labeled ground truth, anchored metadata blocks 48% of error corrections and flips 10.18% of correct judgments toward an assigned wrong label, demonstrating the bias extends beyond numerical scoring to…
Here, we introduce Tree-of-Concerns, a multi-agent framework that deploys specialized skeptic personas, each operating through a category-specific analytical lens, as parallel debate trees to extract unstated limitations from scientific…
Through experiments on ToC-Bench, our benchmark of 414 research papers with 1,905 unstated limitations, sourced from reviewer-reported weaknesses and follow-up citation critiques, we demonstrate that ToC improves precision by 79% and…
Zhuoyang Qian, Biao Wu, Yiran Wang, Chris D Yan, Desan Dai, Liangwei Zheng · Aug 12, 2026 · Citations: 0
Critique EditCoding
We present Spark-to-Paper, an end-to-end research paper generation system implemented as thirteen composable skills inside an existing coding assistant, without requiring a separate agent platform or orchestration service.
Long-form song generation models continue to improve in duration, structural integrity, and acoustic complexity, making reliable aesthetic rewards increasingly important for aligning these models with human preferences.
On the out-of-domain Music Arena benchmark with 733 preference pairs, it achieves the highest accuracy of 71.35%.
Alicia Guerra, Yibo Hu · Aug 5, 2026 · Citations: 0
Critique EditGeneral
Open-ended revisions require a different measurement strategy because answer quality is graded, latent, and judged imperfectly.
We introduce an experimental protocol implemented across a pooled main peer-condition corpus and separately constructed decomposition corpora, allowing us to separate ordinary re-answering, candidate-content exposure, a bundled…
UniMatch is a reference-based evaluation framework for open-ended generation: it segments feedback into feedback units, scores their semantic correspondence under instructor-derived criteria, and aligns them via optimal matching to yield…
Open-ended aesthetic critique is a challenge for multimodal large language models (MLLMs): it has no single correct answer, and most aesthetic evaluation measures models against numeric scores rather than the written critiques people…
We ask whether MLLM critiques are close to human ones, scoring eight open-weight MLLMs from 7B to 397B, plus GPT-5.5, against multiple ranked human critiques for each of 1{,}227 r/photocritique posts under eight prompt conditions.
