“Details are in the source article.”

“This article discusses the development or use of a benchmark called MoReBench, designed to evaluate the moral reasoning capabilities of AI systems.”

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“Current audio evaluation faces three major challenges: (1) audio evaluation lacks a unified framework, with datasets and code scattered across various sources, hindering fair and efficient cross-model comparison”

“Leveraging the LLM-as-a-judge paradigm, Pat-DEVAL introduces Chain-of-Legal-Thought (CoLT), a legally-constrained reasoning mechanism that enforces sequential patent-law-specific analysis.”

“The benchmark demands a lot of model's visual reasoning: they must mentally rotate pieces, count coordinates properly, keep track of each piece's starred square, and determine the relationship between different pieces on the board.”

“The article focuses on making the last mile boring (in the best way).”

“Edit3r directly predicts instruction-aligned 3D edits, enabling fast and photorealistic rendering without optimization or pose estimation.”

“DarkEQA isolates the perception bottleneck by evaluating question answering from egocentric observations under controlled degradations, enabling attributable robustness analysis.”

“ShowUI-$π$ achieves 26.98 with only 450M parameters, underscoring both the difficulty of the task and the effectiveness of our approach.”

“State-of-the-art video models achieve only about 20% POC@1.0 and exhibit a significant outcome-hacking.”

“RAIR presents sufficient challenges even for GPT-5, which achieved the best performance.”

“The best-performing MLLM achieves only 58.0% accuracy.”

“Even the top-performing OpenAI-GPT-5.1 achieves only 62.07% accuracy, and model performance displays a clear gradient distribution.”

“Enhancing the baseline agent with Chain-of-Thought (CoT) reasoning and self-reflection leads to an unexpected performance decrease, suggesting MLLMs exhibit poor context awareness in embodied navigation tasks.”

“RAG assistants leak secrets in up to 26.56% of interactions.”

“OneRec Foundation (1.7B and 8B), a family of models establishing new state-of-the-art (SOTA) results across all tasks in RecIF-Bench.”

“Experimental results demonstrate that existing models still exhibit substantial deficiencies in multi-omics analysis, struggling to reliably distinguish fine-grained biomolecular relation types and to generate faithful, robust pathway-level mechanistic explanations.”

“The central mechanism is energy-grade matching: low-grade WtE thermal output drives absorption cooling to deliver chilled service, thereby displacing baseline cooling electricity.”

“The paper highlights that reasoning-specialized models consistently outperform general-purpose counterparts, indicating the importance of specialized architectures for legal reasoning.”

“The evaluation employs a dynamic sandbox environment that presents agents with candidate tool lists containing distractors, thereby testing their tool selection and discrimination abilities.”

“Probes with a small supervisor model can achieve low calibration error and Brier Skill Score of approx 0.2 estimating edited lines on code generated by models many orders of magnitude larger.”

“The multilingual fine-tuned mT5 baseline outperforms most other approaches including zero-shot LLM performance for most metrics.”

“SourceRank cannot be reliably used to discriminate between benign and malicious packages in real-world scenarios.”

“LLMs comprehensively fail at the quantitative task of predicting financial KPIs in a zero-shot setting.”

“The paper introduces Embodied Reasoning Intelligence Quotient (ERIQ), a large-scale embodied reasoning benchmark in robotic manipulation, and FACT, a flow-matching-based action tokenizer.”

“The AHA framework, leveraging counterfactual hard negative mining, constructs a high-quality preference dataset that forces models to distinguish strict acoustic evidence from linguistically plausible fabrications.”

“FitControler, a learnable plug-in that can seamlessly integrate into modern VTON models to enable customized fit control.”

“PhyAVBench explicitly evaluates models' understanding of the physical mechanisms underlying sound generation.”

“Even minor prompt modifications, such as the substitution or insertion of a single word, can cause substantial degradation in semantic fidelity and temporal dynamics, highlighting critical vulnerabilities in current T2V diffusion models.”

“The system achieved a frame-level action segmentation accuracy of 92.4% and an overall skill classification accuracy of 85.5%.”

“Error detection capability strongly predicts overall robustness (rho=-0.817, p=0.007), indicating this is the critical bottleneck.”

“A positive correlation between LAP and forecast accuracy indicates the presence and magnitude of lookahead bias.”

“Current systems are nominally promptable yet underuse readily available side information.”

“Fine-tuning VLMs on TWIN yields notable gains in fine-grained recognition, even on unseen domains such as art, animals, plants, and landmarks.”

“The paper proposes improvements to MCMC algorithms and compares post-processing methods to stabilize the results of Bayesian profile regression mixture models.”

“Models excel at extracting explicit text, but struggle with deep chemical logic and precise structural recognition.”

“The evaluation protocol jointly measures average accuracy, average cost, and throughput, and builds a ranking score from the harmonic mean of normalized cost and accuracy to enable comparison across router configurations and cost budgets.”

“The RL-GOAL attacker achieves higher mean OGF (up to 2.81 +/- 1.38) across victims, demonstrating its effectiveness.”

“ClinDEF effectively exposes critical clinical reasoning gaps in state-of-the-art LLMs, offering a more nuanced and clinically meaningful evaluation paradigm.”

“MindWatcher can autonomously decide whether and how to invoke diverse tools and coordinate their use, without relying on human prompts or workflows.”

“The paper introduces SpatialMosaic, a comprehensive instruction-tuning dataset featuring 2M QA pairs, and SpatialMosaic-Bench, a challenging benchmark for evaluating multi-view spatial reasoning under realistic and challenging scenarios, consisting of 1M QA pairs across 6 tasks.”

“Leading LLMs showed a uniform 0.00% pass rate on all long-horizon tasks, exposing a fundamental failure in long-term planning.”

“Current models struggle to adapt to the complex visual and cognitive demands of low-altitude scenarios.”

“LLMs generally exhibit a greater affinity for the original text's lexical choices and rhetorical structures, hence tend to be more extractive rather than abstractive in general, compared to humans.”

“Contrastive Learning (CL) induces a more robust feature space for sparse geometry, achieving superior retrieval performance particularly in the 5--10m range.”

“Agents are susceptible to prompt injection in 25% of tasks on average (13% for GPT-5 to 43% for DeepSeek-R1).”

“"AI-slop = generic frameworks, vague conclusions, unsupported claims, or statements that could apply anywhere without changing meaning."”

“Cogniscope enables systematic investigation of multimodal cognitive markers and offers the community a benchmark resource that complements real-world validation studies.”

“The Active Cognition-based Reasoning (ACR) module performs human-like perception of the target via a cognitive task chain and actively reasons about contextually relevant objects, thereby extending VLM cognition through a dynamically updated OLT.”