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Trajectory-Agnostic Asteroid Detection in TESS with Deep Learning

arXiv:2605.12391v1 Announce Type: cross Abstract: We present a novel method for extracting moving objects from TESS data using machine learning. Our approach uses two stacked 3D U-Nets with skip conne

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Model Releases

U-STS-LLM A Unified Spatio-Temporal Steered Large Language Model for Traffic Prediction and Imputation

DGX agent

arXiv:2605.11735v1 Announce Type: new Abstract: The efficient operation of modern cellular networks hinges on the accurate analysis of spatio-temporal traffic data. Mastering these patterns is essenti

model-releasesarxiv-cs-lg

13 May 2026

UHR-Micro: Diagnosing and Mitigating the Resolution Illusion in Earth Observation VLMs

arXiv:2605.12237v1 Announce Type: new Abstract: Vision-Language Models (VLMs) increasingly operate on ultra-high-resolution (UHR) Earth observation imagery, yet they remain vulnerable to a severe scal

UnfoldLDM: Degradation-Aware Unfolding with Iterative Latent Diffusion Priors for Blind Image Restoration

arXiv:2511.18152v3 Announce Type: replace Abstract: Deep unfolding networks (DUNs) combine the interpretability of model-based methods with the learning ability of deep networks, yet remain limited fo

Unlocking UML Class Diagram Understanding in Vision Language Models

arXiv:2605.11634v1 Announce Type: new Abstract: Although Vision Language Models (VLMs) have seen tremendous progress across all kinds of use cases, they still fall behind in answering questions regard

Urban Risk-Aware Navigation via VQA-Based Event Maps for People with Low Vision

arXiv:2605.11782v1 Announce Type: new Abstract: Visual impairment affects hundreds of millions of people worldwide, severely limiting their ability to navigate urban environments safely and independen

VERDI: Single-Call Confidence Estimation for Verification-Based LLM Judges via Decomposed Inference

model-releasesarxiv-cs-cl

arXiv:2605.11334v1 Announce Type: cross Abstract: LLM-as-Judge systems are widely deployed for automated evaluation, yet practitioners lack reliable methods to know when a judge's verdict should be tr

Very Efficient Listwise Multimodal Reranking for Long Documents

arXiv:2605.11864v1 Announce Type: cross Abstract: Listwise reranking is a key yet computationally expensive component in vision-centric retrieval and multimodal retrieval-augmented generation (M-RAG)

Vision-Based Hand Shadowing for Robotic Manipulation via Inverse Kinematics

model-releasesarxiv-cs-ro

arXiv:2603.11383v2 Announce Type: replace Abstract: Teleoperation of low-cost robotic manipulators remains challenging due to the difficulty of retargeting human hand motion to robot joint commands. W

Vision2Code: A Multi-Domain Benchmark for Evaluating Image-to-Code Generation

arXiv:2605.11307v1 Announce Type: new Abstract: Image-to-code generation tests whether a vision-language model (VLM) can recover the structure of an image enough to express it as executable code. Exis

We built SmithDB: the database purpose built for agent observability workloads that now powers many parts of LangSmith. Agent observability …

model-releasesharrison-chase--x

We built SmithDB: the database purpose built for agent observability workloads that now powers many parts of LangSmith. Agent observability presents a challenging data problem. Agent traces can contai

🎉 We published a new AI safety study: shopping agents fall for whimsical attacks and lose money. A whimsical attack is an absurd scenario a…

model-releasesemad-mostaque--x

🎉 We published a new AI safety study: shopping agents fall for whimsical attacks and lose money. A whimsical attack is an absurd scenario a human would never try on another human. In one run, GPT-5.1

Weather-Robust Cross-View Geo-Localization via Prototype-Based Semantic Part Discovery

arXiv:2605.11654v1 Announce Type: new Abstract: Cross-view geo-localization (CVGL), which matches an oblique drone view to a geo-referenced satellite tile, has emerged as a key alternative for autonom

What Does It Mean for a Medical AI System to Be Right?

arXiv:2605.11963v1 Announce Type: new Abstract: This paper examines what it means for a medical AI system to be right by grounding the question in a specific clinical context: the automatic classifica

When you want to move from single agent SQLite on something like QMD, PostgreSQL is a great choice for multi agent and production quality, b…

model-releasesemad-mostaque--x

When you want to move from single agent SQLite on something like QMD, PostgreSQL is a great choice for multi agent and production quality, but not as snappy. So we made it much more snappy with BM25 &

💡 Why did @togethercompute choose NVIDIA Blackwell to serve DeepSeek-V4? Because NVIDIA Blackwell is built for the bottlenecks that matter …

model-releasestogether-ai--x

💡 Why did @togethercompute choose NVIDIA Blackwell to serve DeepSeek-V4? Because NVIDIA Blackwell is built for the bottlenecks that matter most in long-context inference: → KV-cache pressure during de

WildRelight: A Real-World Benchmark and Physics-Guided Adaptation for Single-Image Relighting

arXiv:2605.11696v1 Announce Type: new Abstract: Recent single-image relighting methods, powered by advanced generative models, have achieved impressive photorealism on synthetic benchmarks. However, t

Will Ollama come out with a non-cloud version of Deepseek-v4 Flash?

DeepSeek-v4 Flash through Ollama is currently available as a cloud model, where Ollama's CLI sends API calls to Ollama's hosted version rather than running locally . Local support for DeepSeek V4 Flas

model-releasesr-ollama

XWOD: A Real-World Benchmark for Object Detection under Extreme Weather Conditions

arXiv:2605.11521v1 Announce Type: new Abstract: Autonomous driving and intelligent transportation systems remain vulnerable under extreme weather. The U.S. Federal Highway Administration reports that

YFPO: A Preliminary Study of Yoked Feature Preference Optimization with Neuron-Guided Rewards for Mathematical Reasoning

model-releasesarxiv-cs-cl

arXiv:2605.11906v1 Announce Type: new Abstract: Preference optimization has become an important post-training paradigm for improving the reasoning abilities of large language models. Existing methods

100,000+ Movie Reviews from Kazakhstan: Russian, Kazakh, and Code-Switched Texts

model-releasesarxiv-cs-cl

arXiv:2605.08600v1 Announce Type: new Abstract: We present a new publicly available corpus of 100,502 movie reviews from Kazakhstan collected from kino.kz, spanning 2001-2025 and covering 4,943 unique

3DReflecNet: A Large-Scale Dataset for 3D Reconstruction of Reflective, Transparent, and Low-Texture Objects

arXiv:2605.10204v1 Announce Type: new Abstract: Accurate 3D reconstruction of objects with reflective, transparent, or low-texture surfaces still remains notoriously challenging. Such materials often

A Cognitively Grounded Bayesian Framework for Misinformation Susceptibility

arXiv:2605.09483v1 Announce Type: cross Abstract: In this (work in progress) paper, we present Bounded Pragmatic Listener (or BPL), a cognitively grounded Bayesian framework for modelling susceptibili

A Communication-Theoretic Framework for LLM Agents: Cost-Aware Adaptive Reliability

arXiv:2605.09121v1 Announce Type: cross Abstract: Agents built on large language models (LLMs) rely on a range of reliability techniques, including retry, majority voting, and self-consistency, that h

A Deep Risk Estimator for Known Operator Learning

arXiv:2605.08517v1 Announce Type: cross Abstract: We describe an approach for estimating the statistical risk of deep networks that contain a mix of learned and known operators. Building on the maxima

A Game Theoretic Free Energy Analysis of Higher Order Synergy in Attention Heads of Large Language Models

arXiv:2605.09515v1 Announce Type: new Abstract: Large language models rely on multihead attention, but interactions among heads remain poorly understood. We apply the Game Theoretic Free Energy Princi

A Geometric Perspective on Next-Token Prediction in Large Language Models: Three Emerging Phases

arXiv:2605.09011v1 Announce Type: cross Abstract: We investigate the geometry of predictive information across the layers of large language models (LLMs). We repurpose representation lenses-learned af

A meshfree exterior calculus for generalizable and data-efficient learning of physics from point clouds

arXiv:2605.08436v1 Announce Type: cross Abstract: We introduce a meshfree exterior calculus (MEEC) for learning structure-preserving descriptions of physics on point clouds, and use it to build MEEC-N

A new initialisation to Control Gradients in Sinusoidal Neural network

arXiv:2512.06427v2 Announce Type: replace Abstract: Proper initialisation strategy is of primary importance to mitigate gradient explosion or vanishing when training neural networks. Yet, the impact o

A Quantum Inspired Variational Kernel and Explainable AI Framework for Cross Region Solar and Wind Energy Forecasting

arXiv:2605.09032v1 Announce Type: cross Abstract: Reliable short horizon forecasting of solar and wind generation is a structural prerequisite of any modern power system yet most published forecasters

A Stability Benchmark of Generative Regularizers for Inverse Problems

arXiv:2605.10076v1 Announce Type: cross Abstract: Generative (diffusion) priors demonstrate remarkable performance in addressing inverse problems in imaging. Yet, for scientific and medical imaging, i

A startup wants to pull magnesium from seawater without torching the environment. Another wants to take small language models to the podium …

model-releasesai21-labs--x

A startup wants to pull magnesium from seawater without torching the environment. Another wants to take small language models to the podium for enterprise customers. Today @jason and @alex sat down wi

A Unified Representation of Neural Networks Architectures

arXiv:2512.17593v3 Announce Type: replace Abstract: In this paper we consider the limiting case of neural networks (NNs) architectures when the number of neurons in each hidden layer and the number of

Accelerating Power Method with Fast Sketching for Stronger Low-Rank Approximation

arXiv:2605.09755v1 Announce Type: cross Abstract: The power method is one of the most fundamental tools for extracting top principal components from data through low-rank matrix approximation. Yet, wh

Acceptance Cards:A Four-Diagnostic Standard for Safe Fine-Tuning Defense Claims

arXiv:2605.10575v1 Announce Type: cross Abstract: Safe fine-tuning defenses are often endorsed on the basis of a held-out gap reduction, but the same reduction can come from sampling noise, subject ar

Action-Guided Attention for Video Action Anticipation

arXiv:2603.01743v2 Announce Type: replace Abstract: Anticipating future actions in videos is challenging, as the observed frames provide only evidence of past activities, requiring the inference of la

ACWM-Phys: Investigating Generalized Physical Interaction in Action-Conditioned Video World Models

arXiv:2605.08567v1 Announce Type: new Abstract: Action-conditioned world models (ACWMs) have shown strong promise for video prediction and decision-making. However, existing benchmarks are largely res

AdamFLIP: Adaptive Momentum Feedback Linearization Optimization for Hard Constrained PINN Training

arXiv:2605.08408v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) provide a flexible framework for solving forward and inverse problems governed by partial differential equation

AdaPaD: Adaptive Parallel Deflation for PEFT with Self-Correcting Rank Discovery

arXiv:2605.10741v1 Announce Type: new Abstract: Fine-tuning large language models with LoRA requires choosing a rank r before training starts. Existing approaches either extract rank-1 components sequ

AdaPreLoRA: Adafactor Preconditioned Low-Rank Adaptation

arXiv:2605.08734v1 Announce Type: cross Abstract: Low-Rank Adaptation (LoRA) reparameterizes a weight update as a product of two low-rank factors, but the Jacobian J_{G} of the generator mapping the f

Adaptive Multi-view Graph Contrastive Learning via Fractional-order Neural Diffusion Networks

arXiv:2511.06216v4 Announce Type: replace Abstract: Graph contrastive learning (GCL) learns node and graph representations by contrasting multiple views of the same graph. Existing methods typically r

Adversary-Robust Learning from Fully Asynchronous Directional Derivative Estimates

arXiv:2605.09337v1 Announce Type: new Abstract: We propose FAR-SIGN (Fully Asynchronous Robust optimization via SIGNed directional projections) for adversary-resilient learning in parameter-server--wo

Agent-ValueBench: A Comprehensive Benchmark for Evaluating Agent Values

arXiv:2605.10365v1 Announce Type: new Abstract: Autonomous agents have rapidly matured as task executors and seen widespread deployment via harnesses such as OpenClaw. Safety concerns have rightly dra

AgentCollabBench: Diagnosing When Good Agents Make Bad Collaborators

arXiv:2605.08647v1 Announce Type: cross Abstract: Multi-agent systems achieve state-of-the-art outcomes through peer collaboration. However, when an agent in the pipeline silently drops a constraint,

AgentForesight: Online Auditing for Early Failure Prediction in Multi-Agent Systems

arXiv:2605.08715v1 Announce Type: cross Abstract: LLM-based multi-agent systems are increasingly deployed on long-horizon tasks, but a single decisive error is often accepted by downstream agents and

Agentic MIP Research: Accelerated Constraint Handler Generation

arXiv:2605.09186v1 Announce Type: new Abstract: Mixed-integer programming (MIP) research is both mathematically sophisticated and engineering-intensive: testing an algorithmic hypothesis within a bran

Agentic Performance at the Edge: Insights from Benchmarking

arXiv:2605.10384v1 Announce Type: new Abstract: Agentic artificial intelligence (AI) is a natural fit for Internet of Things (IoT) and edge systems, but edge deployments are often constrained to model

AgentPSO: Evolving Agent Reasoning Skill via Multi-agent Particle Swarm Optimization

arXiv:2605.08704v1 Announce Type: new Abstract: Multi-agent reasoning has shown promise for improving the problem-solving ability of large language models by allowing multiple agents to explore divers