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OpenAI releases MentalHealthBench, an open benchmark to evaluate AI responses in realistic mental health conversations, developed with 80+ licensed experts (OpenAI)

OpenAI: OpenAI releases MentalHealthBench, an open benchmark to evaluate AI responses in realistic mental health conversations, developed with 80+ licensed experts — An open benchmark developed with m

model-releasestechmeme

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Industry

OpenAI says ChatGPT Voice can now be powered by GPT-6 Astra, Sol, and Luna, use plugins like email and calendar, and be used in ChatGPT Work on web and mobile (@openai)

DGX agent

@openai: OpenAI says ChatGPT Voice can now be powered by GPT-6 Astra, Sol, and Luna, use plugins like email and calendar, and be used in ChatGPT Work on web and mobile — We heard you loud and clear. C

industrytechmeme

23 Sept 2026

OpenAI says it will give its AI cyber defense system Daybreak and GPT-5.6 Sol to the Ukrainian government for free to help it protect civilian infrastructure (Zoe Kleinman/BBC)

Zoe Kleinman / BBC: OpenAI says it will give its AI cyber defense system Daybreak and GPT-5.6 Sol to the Ukrainian government for free to help it protect civilian infrastructure — The tech giant OpenA

model-releasestechmeme

OpenQlaw: An Agentic AI Assistant for Analysis of 2D Quantum Materials

arXiv:2603.17043v2 Announce Type: replace Abstract: Physics-aware multimodal large language models (MLLMs) can localize and characterize two-dimensional (2D) material flakes from optical microscopy im

local-aiarxiv-cs-cv

Optimal Sequential Annotations for Off-Policy Evaluation

arXiv:2609.26707v1 Announce Type: cross Abstract: Offline reinforcement learning and off-policy evaluation evaluates dynamic treatment rules based on retrospectively collected data prior to deployment

safetyarxiv-cs-lg

Optimal Tradeoffs Between Network Size and Parameter Magnitude in Neural Approximation and Minimax Regression

arXiv:2609.25710v1 Announce Type: cross Abstract: The statistical accuracy of neural networks depends on both their approximation power and the complexity of the class fitted from data. While increasi

Optimizing Canaries for Privacy Auditing with Metagradient Descent

arXiv:2507.15836v2 Announce Type: replace Abstract: In this work we study black-box privacy auditing, where the goal is to lower bound the privacy parameter of a differentially private learning algori

Optimizing Denoising Trajectories in dLLMs: A Lightweight Evolutionary Heuristic Approach

model-releasesarxiv-cs-cl

arXiv:2609.26052v1 Announce Type: new Abstract: Diffusion Large Language Models (dLLMs) have recently emerged as a promising alternative to conventional Auto-Regressive (AR) Large Language Models (LLM

OptiSkill: A Hierarchical and Evolving SkillBank for LLM-Based Optimization Modeling

arXiv:2609.22987v1 Announce Type: new Abstract: Automated operations research (OR) modeling requires LLMs to translate natural-language decision problems into correct mathematical programs. Existing m

Agents

Oracle puts database security controls beneath AI agents

Database security controls are moving closer to enterprise data as artificial intelligence creates new access paths around traditional application defenses. The aim is to enforce authorization regardl

agentssiliconangle

Agents

Oracle shifts agent controls toward data-layer security

Data-layer security is becoming more important as automated systems gain broader access to sensitive information and business processes. Controls designed for predictable applications may not be enoug

agentssiliconangle

Out today: Nemotron 3 Diarization, so you can implement speaker detection in your voice applications. 🗣️✅ And it's available day-0 on trans…

model-releasesclem-delangue--x

Out today: Nemotron 3 Diarization, so you can implement speaker detection in your voice applications. 🗣️✅ And it's available day-0 on transformers and @Dell Enterprise Hub! Enterprises can implement o

Applications

OV-MAP: Open-Vocabulary Zero-Shot 3D Instance Segmentation Map for Robots

arXiv:2506.11585v3 Announce Type: replace Abstract: We introduce OV-MAP, a novel approach to open-world 3D mapping for mobile robots by integrating open-features into 3D maps to enhance object recogni

applicationsarxiv-cs-cv

PAANI : On Device Visual Evidence Fusion and Explainable Guidance for River Robot Simulation

arXiv:2609.22353v1 Announce Type: new Abstract: Mobile river monitoring robots must interpret obstacles and water boundaries that geographic waypoints alone cannot describe. On resource constrained pl

PACE-dLLM: Elastic Block Decoding via Confidence Cliff Estimation for Diffusion Language Models

arXiv:2609.26249v1 Announce Type: new Abstract: Diffusion language models (dLLMs), such as LLaDA and Dream, have become competitive with autoregressive (AR) LLMs in generation quality while supporting

researcharxiv-cs-cl

PACT: From Credit Assignment to Critic Alignment

arXiv:2609.26355v1 Announce Type: new Abstract: Reinforcement learning has become a central component of large language model (LLM) post-training, yet token-level credit lacks a generally accepted mat

safetyarxiv-cs-lg

PAKT: Physically-Aligned Kinesthetic Teaching for Reinforcement Learning

arXiv:2609.25630v1 Announce Type: new Abstract: Real-world reinforcement learning (RL) systems still struggle with the demands of contact-rich industrial manipulation, including micrometer-level preci

Parameterized Dense-Sparse Fusion for Hybrid Retrieval: Tuning a Rank-Score Mix on BEIR SciFact with Qdrant

model-releasesarxiv-cs-ai

arXiv:2609.22770v2 Announce Type: cross Abstract: We study a parameterized hybrid ranker that fuses a dense embedding list and a sparse lexical list. The method has a small, explicit parameter vector:

PARTE: Plane-Assisted Robust Transformation Estimation for Point Cloud Registration

arXiv:2609.25375v1 Announce Type: new Abstract: Global point-cloud registration remains challenging when limited overlap, repetitive geometry, and sensor noise produce correspondence sets dominated by

researcharxiv-cs-ro

Partially Observed Sparse Graphs: The Unknown Sampling Rate is a Tail Index

arXiv:2609.26199v1 Announce Type: new Abstract: A large graph is often available only in part: a crawl stopped by its budget, a panel, a partial dump. When the sampled fraction s is known by design th

PartLLM: A Unified Multimodal Foundation for 3D Part Segmentation

arXiv:2609.25832v1 Announce Type: new Abstract: Part segmentation is a fundamental problem in computer graphics and 3D vision. Recent works have expanded 3D part segmentation beyond fixed taxonomies,

researcharxiv-cs-cv

Partner-Specific Affective Precision in Social Active Inference

arXiv:2609.24876v1 Announce Type: new Abstract: In multi-agent social settings, model reliability varies across relationships. Beyond inferring what others will do, an agent must calibrate how confide

Passes Alone, Fails Together: Benchmarking Semantic Coordination in Parallel LLM-Agent Development

model-releasesarxiv-cs-cl

arXiv:2609.25396v1 Announce Type: new Abstract: Parallel coding agents can produce patches that work alone but fail when merged. This happens when one agent changes an interface or rule that another a

PatchKV: Efficient KV Cache Recovery for Dynamically Edited LLM Contexts

arXiv:2609.26219v1 Announce Type: cross Abstract: Long-running LLM agent workflows often revise interior context spans while retaining long suffixes. Although suffix tokens remain unchanged, altered c

local-aiarxiv-cs-lg

Peerify: Benchmarking Peer-Review Claim Verification

model-releasesarxiv-cs-cl

arXiv:2609.25046v1 Announce Type: new Abstract: Peer review plays a central role in scholarly publishing, yet verifying whether reviewer claims are supported by manuscript evidence remains a largely m

Penalized Nonreversible Langevin for Constrained Sampling

arXiv:2609.25381v1 Announce Type: cross Abstract: We propose penalized nonreversible Langevin algorithms for sampling from pi(x)propto e^{-f(x)}mathbf 1_{mathcal C}(x), where mathcal Csubsetmathbb R^d

Perhaps the highest quality mainline quants of Qwen3.8 27B?

model-releasesr-localllama

I am proud to release these quants of Qwen 3.8 27B. They beat the excellent ISTA and Unsloth quants byte-for-byte on three corpora. Both KLD and top 1% were tested 3x. It took a week of continuous GPU

PermuFormer: Multi-Task Pretraining for Permutation Representation in Algebraic Combinatorics

arXiv:2609.25438v1 Announce Type: new Abstract: Diverse pretraining has been shown to be an effective method for learning reusable, domain-aware representations that provide a starting point for fine-

PERSONAWEAVER: Controllable Diversity Beyond Conventional Archetypes in Procedural Character Generation

arXiv:2609.26629v1 Announce Type: new Abstract: Procedural character generation aims to populate games, simulations, and other virtual worlds with diverse characters. Large language models (LLMs) offe

researcharxiv-cs-cl

phi-RIE: From Photorealistic Reconstruction to Interactive Environments

model-releasesarxiv-cs-ro

arXiv:2609.26795v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) can reconstruct a captured scene photorealistically, but the resulting representation does not by itself support physical i

PhysAI-Bench: A Benchmark for LLM-Based Agentic Decision-Making in Autonomous UAV-Centric Physical AI

model-releasesarxiv-cs-ai

arXiv:2609.23695v1 Announce Type: new Abstract: Recent advances in Physical AI have accelerated the use of foundation models in autonomous systems such as unmanned aerial vehicles (UAVs), which must p

Physics-guided deep metric learning with continuous time embeddings for open-world radar pulse de-interleaving

arXiv:2609.25057v1 Announce Type: cross Abstract: Radar pulse de-interleaving is a foundational Electronic Support Measures (ESM) task that aims to separate chronologically interleaved pulse streams f

PhyVisGen: Physically and Visually High-Fidelity Robotic Manipulation Data Generation

arXiv:2609.25653v1 Announce Type: new Abstract: Large-scale manipulation demonstrations are essential for learning robust visuomotor policies, yet real-world data collection is expensive and difficult

Pi agent qwen 3.8 flash next plays Baldur's Gate 2

model-releasesr-localllama

If like me you enjoyed classics like Baldur's Gate 2, this is a small fun experiment. For anyone interested: https://www.youtube.com/live/8FhPfRKTucw?si=PMIVdHbZ-31PNwZD Qwen 3.8 Flash Next has amazin

PICPIs: Prediction-Interval-Conditional Prediction Intervals

arXiv:2609.25388v1 Announce Type: cross Abstract: A classical question in statistics is which observable quantities to condition on when drawing inferences about unobservable targets. For conformal pr

local-aiarxiv-cs-lg

PINNForge: Execution-Grounded Evolutionary Design of Physics-Informed Neural Networks for PDE Solving via Large Language Models

arXiv:2609.23023v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) require coordinated choices over network representation, sampling, loss construction, and optimization, while e

researcharxiv-cs-ai

Pinocchio: Fast Uncertainty Estimates for Black-Box Language Models

arXiv:2609.24881v2 Announce Type: new Abstract: In high-stakes decision-making applications of large language models (LLMs), practitioners require not only accurate LLMs but also uncertainty estimates

researcharxiv-cs-ai

PLAT: Sparse Timed Keyframe Motion Tracking for Humanoid Control via Privileged Latent Transition Learning

arXiv:2609.25754v1 Announce Type: new Abstract: Humanoid motion tracking policies rely on dense frame-by-frame references, limiting their use as high-level motion controllers for planning and interact

Point Diffusion Mamba: Unified Diffusion-State-Space Modeling for Single-View 3D Reconstruction under Data Scarcity

arXiv:2609.25538v1 Announce Type: new Abstract: While single-view 3D reconstruction has seen significant progress, extrapolating complex 3D structures from inherently ambiguous 2D observations remains

researcharxiv-cs-cv

Polyak-Type Extragradient Methods for Monotone Root-Finding Problems

arXiv:2609.26581v1 Announce Type: cross Abstract: We study Polyak-type step-size selection for extragradient methods for solving deterministic and stochastic monotone root-finding problems. We show th

Polynomial Scaling is Possible For Neural Operator Approximations of Structured Families of BSDEs

arXiv:2410.14788v4 Announce Type: replace-cross Abstract: Neural operator (NO) architectures learn nonlinear maps between infinite-dimensional function spaces and are widely used to accelerate simulat

safetyarxiv-cs-lg

PP-Net: A Hybrid Physical-Prior Neural Network for Scattered Light Removal in Biomedical Images on Embedded Devices

arXiv:2609.26474v1 Announce Type: cross Abstract: Scattered light is common in biomedical images, yet its removal remains challenging. The difficulty arises from three aspects: first, aligned scattere

Predict Before You Step: Auditable Occupancy Forecasting for Dynamic Obstacle Avoidance under Sparse Guidance

arXiv:2609.25969v1 Announce Type: new Abstract: Legged robots under sparse waypoint guidance must avoid moving obstacles using partial, rapidly changing LiDAR observations. We present LOOP (Latent-rec

Applications

Predicting Postprandial Glycemic Response from Meal Images, Clinical Variables, and Gut Microbiome Information

arXiv:2609.24453v1 Announce Type: new Abstract: Predicting postprandial glycemic response (PPGR) is fundamental to personalized nutrition and type 2 diabetes management, yet existing approaches typica

applicationsarxiv-cs-ai

Predictive Uncertainty for Neural CAE Surrogates

arXiv:2609.25430v1 Announce Type: new Abstract: Neural surrogates can substantially accelerate computer-aided engineering (CAE) workflows, but their use in design requires uncertainty estimates that r

PreGS: A Parameter-Transfer-Based Multi-Expert Graph Neural Network for Node Classification

arXiv:2609.26310v1 Announce Type: new Abstract: Graph neural networks have achieved strong performance in node classification by aggregating information from graph neighborhoods. However, a single agg

Pretraining of Medical Visual Encoders Toward Multi-modal Large Language Models

arXiv:2609.23860v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) commonly reuse visual encoders pretrained with CLIP, although the features of these ViTs are ultimately consume

PreUnlearn: Auditing Collateral Knowledge Damage Before Large Language Model Unlearning

arXiv:2606.18473v2 Announce Type: replace Abstract: Machine unlearning for large language models (LLMs) aims to remove specified knowledge while preserving the rest of the model's capabilities. Howeve

researcharxiv-cs-cl