model releases

Neural Posterior Estimation of Terrain Parameters from Radar Sounder Data

arXiv:2605.08179v1 Announce Type: cross Abstract: Radar sounders are electromagnetic instruments that can probe deep into the subsurface of Earth and other planetary bodies by processing the echo of t

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Neural Weight Norm = Kolmogorov Complexity

DGX agent

arXiv:2605.10878v1 Announce Type: new Abstract: Why does weight decay work? We prove that, in any fixed-precision regime, the smallest weight norm of a looped neural network outputting a binary string

model-releasesarxiv-cs-lg

12 May 2026

NeuralBench: A Unifying Framework to Benchmark NeuroAI Models

arXiv:2605.08495v1 Announce Type: new Abstract: Deep learning and large public datasets have recently catalyzed the proliferation of AI models for processing brain recordings. However, systematically

NeurIPS Should Require Reproducibility Standards for Frontier AI Safety Claims

arXiv:2605.08192v1 Announce Type: cross Abstract: Frontier AI safety claims - published assertions that a highly capable general-purpose model is below a threshold of concern, adequately mitigated, or

New Signadot skill lets Claude Code, Codex and Cursor validate changes in live Kubernetes environments

model-releasessiliconangle

Microservices testing company Signadot Inc. today launched /signadot-validate, a new skill that lets coding agents such as Anthropic PBC’s Claude Code, OpenAI Group PBC’s Codex and Cursor validate the

Normalization Equivariance for Arbitrary Backbones, with Application to Image Denoising

arXiv:2605.08193v1 Announce Type: cross Abstract: Normalization Equivariance (NE), equivariance to global contrast and brightness transforms, improves robustness to distribution shift in image-to-imag

Not All Proofs Are Equal: Evaluating LLM Proof Quality Beyond Correctness

model-releasesarxiv-cs-cl

arXiv:2605.10379v1 Announce Type: new Abstract: Large language models (LLMs) have become capable mathematical problem-solvers, often producing correct proofs for challenging problems. However, correct

Omni-DeepSearch: A Benchmark for Audio-Driven Omni-Modal Deep Search

arXiv:2605.08762v1 Announce Type: cross Abstract: Current omni-modal benchmarks mainly evaluate models under settings where multiple modalities are provided simultaneously, while the ability to start

Omni-Persona: Systematic Benchmarking and Improving Omnimodal Personalization

arXiv:2605.09996v1 Announce Type: new Abstract: While multimodal large language models have advanced across text, image, and audio, personalization research has remained primarily vision-language, wit

One for All: A Non-Linear Transformer can Enable Cross-Domain Generalization for In-Context Reinforcement Learning

arXiv:2605.09727v1 Announce Type: cross Abstract: A central challenge in reinforcement learning (RL) is to learn models that generalize beyond the tasks on which they are trained, a goal traditionally

OpenAI contacted me to say “Study Mode is still live and accessible via /study and /learn shortcuts” so that’s good, although the official s…

model-releasesethan-mollick--x

OpenAI contacted me to say “Study Mode is still live and accessible via /study and /learn shortcuts” so that’s good, although the official study mode page doesn’t mention that. (I don’t think slash co

OpenSGA: Efficient 3D Scene Graph Alignment in the Open World

arXiv:2605.10484v1 Announce Type: new Abstract: Scene graph alignment establishes object correspondences between two 3D scene graphs constructed from partially overlapping observations. This enables e

OPT-BENCH: Evaluating the Iterative Self-Optimization of LLM Agents in Large-Scale Search Spaces

arXiv:2605.08904v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities in reasoning and tool use. However, the fundamental cognitive faculties essential

Optimal FALQON for Quantum Approximate Optimization via Layer-wise Parameter Tuning

arXiv:2605.08332v1 Announce Type: cross Abstract: Feedback-based adaptive quantum optimization (FALQON) is a promising approach for solving combinatorial problems on noisy intermediate-scale quantum (

Optimality of Sub-network Laplace Approximations: New Results and Methods

arXiv:2605.09075v1 Announce Type: cross Abstract: Although the Laplace approximation offers a simple route to uncertainty quantification in deep neural networks, its reliance on inverting large Hessia

Optimised Support Vector Regression for California Housing Price Prediction: The Critical Role of Feature Engineering and Hyperparameter Tuning

arXiv:2605.08660v1 Announce Type: new Abstract: In the recent literature, Support Vector Regression (SVR) has been cited as one of the weakest performers on the California Housing benchmark dataset, w

Optimized Culprit Identification Using Mobilenet and Attention Mechanisms

arXiv:2605.08169v1 Announce Type: cross Abstract: Automated culprit identification in surveillance systems is a critical task that requires high accuracy along with computational efficiency for real-t

Oracle Poisoning: Corrupting Knowledge Graphs to Weaponise AI Agent Reasoning

arXiv:2605.09822v1 Announce Type: cross Abstract: We define Oracle Poisoning, an attack class in which an adversary corrupts a structured knowledge graph that AI agents query at runtime via tool-use p

OracleTSC: Oracle-Informed Reward Hurdle and Uncertainty Regularization for Traffic Signal Control

arXiv:2605.08516v1 Announce Type: new Abstract: Transparent decision-making is essential for traffic signal control (TSC) systems to earn public trust. However, traditional reinforcement learning-base

OrderFusion: Encoding Orderbook for End-to-End Probabilistic Intraday Electricity Price Forecasting

arXiv:2502.06830v5 Announce Type: replace-cross Abstract: Probabilistic intraday electricity price forecasting is becoming increasingly important for short-term power-system operation. With increasing

OTora: A Unified Red Teaming Framework for Reasoning-Level Denial-of-Service in LLM Agents

arXiv:2605.08876v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed as autonomous agents that execute tool-augmented, multi-step tasks, where latency is a critical f

Overconfident and Blind to Details: Fixing Prompt Insensitivity with Abductive Preference Learning

model-releasesarxiv-cs-cl

arXiv:2510.09887v2 Announce Type: replace Abstract: Vision and language models frequently ignore semantically critical input edits, defaulting to pretraining priors. For example, models will confident

Pairwise is Not Enough: Hypergraph Neural Networks for Multi-Agent Pathfinding

arXiv:2602.06733v2 Announce Type: replace-cross Abstract: Multi-Agent Path Finding (MAPF) is a representative multi-agent coordination problem, where multiple agents are required to navigate to their

PaperFit: Vision-in-the-Loop Typesetting Optimization for Scientific Documents

arXiv:2605.10341v1 Announce Type: new Abstract: A LaTeX manuscript that compiles without error is not necessarily publication-ready. The resulting PDFs frequently suffer from misplaced floats, overflo

Parallel Multi-Circuit Quantum Feature Fusion in Hybrid Quantum-Classical Convolutional Neural Networks for Breast Tumor Classification

arXiv:2512.02066v2 Announce Type: replace-cross Abstract: Quantum machine learning has emerged as a promising approach to improve feature extraction and classification tasks in high-dimensional data d

Parameter-Efficient Neuroevolution for Diverse LLM Generation: Quality-Diversity Optimization via Prompt Embedding Evolution

arXiv:2605.09781v1 Announce Type: cross Abstract: Large Language Models exhibit mode collapse, producing homogeneous outputs that fail to explore valid solution spaces. We present QD-LLM, a framework

parameter golf was a blast. 2,000+ submissions. 1,000+ verified github accounts. ideas ranging from quantization and depth recurrence to TTT…

parameter golf was a blast. 2,000+ submissions. 1,000+ verified github accounts. ideas ranging from quantization and depth recurrence to TTT LoRA, SSMs, H-nets, JEPA, and more. autoresearch made itera

model-releasesopenai--x

Parameterized Complexity of Stationarity Testing for Piecewise-Affine Functions and Shallow CNN Losses

arXiv:2605.10219v1 Announce Type: cross Abstract: We study the parameterized complexity of testing approximate first-order stationarity at a prescribed point for continuous piecewise-affine (PA) funct

Path-Based Gradient Boosting for Graph-Level Prediction

arXiv:2605.08102v1 Announce Type: new Abstract: We propose PathBoost, a gradient tree boosting method for graph-level classification and regression that learns discriminative path-based features direc

PDEAgent-Bench: A Multi-Metric, Multi-Library Benchmark for PDE Solver Generation

arXiv:2605.09636v1 Announce Type: new Abstract: PDE-to-solver code generation aims to automatically synthesize executable numerical solvers from partial differential equation (PDE) specifications. Thi

Per-Loss Adapters for Gradient Conflict in Physics-Informed Neural Networks

arXiv:2605.10136v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) train a single neural approximation by minimizing multiple physics- and data-derived losses, but the gradients

Personal Visual Context Learning in Large Multimodal Models

arXiv:2605.10936v1 Announce Type: new Abstract: As wearable devices like smart glasses integrate Large Multimodal Models (LMMs) into the continuous first-person visual streams of individual users, the

Personalized Alignment Revisited: The Necessity and Sufficiency of User Diversity

arXiv:2605.09119v1 Announce Type: cross Abstract: Personalized alignment aims to adapt large language models to heterogeneous user preferences, yet the precise theoretical conditions for its statistic

PHIDA: Persistence-Guided Node-to-Cluster Mapping for Online Clustering

arXiv:2605.08673v1 Announce Type: new Abstract: Online clustering methods that adaptively create and update nodes as data arrive often make node learning explicit, whereas the mapping from the learned

Phoenix-VL 1.5 Medium Technical Report

arXiv:2605.10391v1 Announce Type: cross Abstract: We introduce Phoenix-VL 1.5 Medium, a 123B-parameter natively multimodal and multilingual foundation model, adapted to regional languages and the Sing

PhyGround: Benchmarking Physical Reasoning in Generative World Models

arXiv:2605.10806v1 Announce Type: cross Abstract: Generative world models are increasingly used for video generation, where learned simulators are expected to capture the physical rules that govern re

PINS: Proximal Iterations with Sparse Newton and Sinkhorn for Optimal Transport

arXiv:2502.03749v2 Announce Type: replace Abstract: Optimal transport (OT) is a widely used tool in machine learning, but computing high-accuracy solutions for large instances remains costly. Entropic

Pix2Fact: When Vision Is Not Enough -- Benchmarking Fine-Grained VQA with Web Verification on High-Resolution Real-World Scenes

arXiv:2602.00593v2 Announce Type: replace Abstract: Despite progress on general tasks, vision-language models (VLMs) still struggle with challenges that demand both fine-grained visual grounding and e

PlantMarkerBench: A Multi-Species Benchmark for Evidence-Grounded Plant Marker Reasoning

model-releasesarxiv-cs-cl

arXiv:2605.10032v1 Announce Type: new Abstract: Cell-type-specific marker genes are fundamental to plant biology, yet existing resources primarily rely on curated databases or high-throughput studies

PolarVSR: A Unified Framework and Benchmark for Continuous Space-Time Polarization Video Reconstruction

arXiv:2605.10275v1 Announce Type: new Abstract: Polarimetric imaging captures surface polarization characteristics, such as the Degree of Linear Polarization (DoLP) and the Angle of Polarization (AoP)

Polymath: A Challenging Multi-modal Mathematical Reasoning Benchmark

arXiv:2410.14702v2 Announce Type: replace Abstract: Multi-modal Large Language Models (MLLMs) exhibit impressive problem-solving abilities in various domains, but their visual comprehension and abstra

Position: AI Security Policy Should Target Systems, Not Models

arXiv:2605.09504v1 Announce Type: cross Abstract: We present swarm-attack, an open-source adversarial testing framework in which multiple lightweight LLM agents coordinate through shared memory, paral

Position: Stop Evaluating AI with Human Tests, Develop Principled, AI-specific Tests instead

arXiv:2507.23009v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have achieved remarkable results on a range of standardized tests originally designed to assess human cognitive a

PPU-Bench:Real World Benchmark for Personalized Partial Unlearning in Vision Language Models

arXiv:2605.08800v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) may memorize sensitive cross-modal information during pretraining. However, existing MLLM unlearning benchmar

PrAg-PO: Prompt Augmented Policy Optimization for Robust and Diverse Mathematical Reasoning

arXiv:2602.03190v3 Announce Type: replace-cross Abstract: Reinforcement learning algorithms such as group-relative policy optimization (GRPO) have shown strong potential for improving the mathematical

Prediction Bottlenecks Don't Discover Causal Structure (But Here's What They Actually Do)

arXiv:2605.09169v1 Announce Type: cross Abstract: A Mamba state-space model trained only for next-step prediction appears to recover Granger-causal structure through a simple readout S = |W_{out} W_{i

PrepBench: How Far Are We from Natural-Language-Driven Data Preparation?

arXiv:2605.08687v1 Announce Type: cross Abstract: Data preparation is a central and time-consuming stage in data analysis workflows. Traditionally, commercial tools have relied on graphical user inter

Preserve and Personalize: Personalized Text-to-Image Diffusion Models without Distributional Drift

arXiv:2505.19519v3 Announce Type: replace Abstract: Personalizing text-to-image diffusion models involves integrating novel visual concepts from a small set of reference images while retaining the mod