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Researchers introduced SPARC-Rad, a manually curated multimodal benchmark dataset and evaluation pipeline for assessing spatial and anatomical reasoning in radiology vision-language models (VLMs). The dataset includes 30…

Researchers introduced TreeProbe, the first cultural-bias benchmark for Tibetan medicine, containing 4,719 expert-adjudicated items covering 467 diseases and 10 subtasks, and found that current large language models exhi…

Researchers introduced MedUPSQA, a dataset of 21,874 mid-stream clinical decision points from 5,535 real case reports, and MedUPS, an alignment framework that uses reinforcement learning to improve next-step accuracy in …

Researchers propose RSTG (Recovering Learning Signals via Adaptive Teacher Guidance), a method that selectively applies on-policy distillation to negative zero-variance prompts in reinforcement learning with verifiable r…

Researchers introduced OoO-Spec, an out-of-order semantic speculation method that speeds up LLM tool calling by predicting function choices and argument values in parallel. Across seven targets and three benchmarks, OoO-…

Opt.Gear, a new foundation model family from an unnamed research team, achieves up to 4.9x faster prefill and decoding speeds on NPUs compared to similar-scale models, with dense models of 1M, 270M, and 1B parameters sup…

Researchers introduced DeBERTa-Sentinel, an AI-generated text detection framework using DeBERTa-v3's disentangled attention, achieving 98.21% validation accuracy and 97.53% test accuracy on the GLC-AIText dataset of 28,0…

AI is moving workers up the value chain, but it may also be deskilling them, according to a blog post by Marcus on marcusoft.net. As AI agents take over writing, coding, and creation, humans become managers who oversee a…

Snyk Secrets, an ML-powered secrets detection engine from Snyk's acquisition of BitPatrol, is now generally available as part of the Snyk AI Security Platform, aiming to reduce false positives and integrate into agentic …

At Black Hat USA 2026, Snyk announced the general availability of Evo Continuous Offensive Security (COS), an autonomous, AI-powered pentesting solution designed to close the gap between periodic manual pentests and cont…

Snyk introduced Agentic AppSec with two new capabilities: Remediation Agent, now in public preview, and Malicious Code Defense, in private preview. The Remediation Agent automatically fixes vulnerabilities and shows a ~1…

A new arXiv preprint (2608.00246v1) proposes a retain-aware localization method for machine unlearning that considers parameter importance to both forgotten and retained data, reducing collateral damage to semantically s…

A new arXiv preprint (2608.00301v1) proves that error-penalized scoring rules, which reward correct answers with +1, penalize wrong ones with -λ, and give 0 for abstention, can cause KL-anchored gradient learners to drif…

Researchers introduced a flow-map learning (FML) framework to model unknown nonlocal partial differential equations (PDEs) directly from solution data, bypassing explicit evaluation of nonlocal operators. The method lear…

Researchers introduced DLLM-TTS, a text-to-speech framework using block discrete diffusion over X-Codec2 neural audio codec tokens, achieving a real-time factor of 0.15 with a 0.6B-parameter model trained on 20K hours, a…

Researchers introduced LLantia, an automated method using large language models to infer neural circuit function from connectome data, and applied it to the adult fruit fly brain, inferring cell type functions for all ce…

Researchers at arXiv introduced a novel pre-training method for logographic character recognition that uses semantic-based contrastive learning to improve visual representations on imbalanced datasets. The method, which …

Researchers introduced DE-NER, a dialogue elicitation framework that improves zero-shot Named Entity Recognition by leveraging the chatting ability of Large Language Models, achieving an average improvement of 3.75% F1 p…

Researchers propose a multimodal machine-learning framework for calibration monitoring and quality assessment in archaeological digitisation, integrating photogrammetric 3D reconstruction, hyperspectral imaging, X-ray fl…

A new arXiv study (2608.00077v1) audits visual-token pruning in OCR-critical multimodal large language models (MLLMs), finding that accuracy alone misses failures where correct answers lack local token provenance. On loc…