Search: “model-releases”

WorldRoamBench: An Open-World Benchmark for Long-Horizon Stability of Interactive World Models

arXiv:2606.31672v1 Announce Type: cross Abstract: Despite rapid progress in interactive world models (IWMs), existing benchmarks evaluate action following only at trajectory level and ignore memory an

Xiaomi-GUI-0 Technical Report

DGX agent

arXiv:2606.31410v1 Announce Type: new Abstract: Graphical user interface (GUI) agents build on vision-language models to complete user tasks end-to-end in real applications through interface actions s

model-releasesarxiv-cs-ai

1 Jul 2026

Yes! Pre-classifying routers are going to result in a lot of bad work because routing is hard and tend to underestimate the value of intelli…

model-releasesethan-mollick--x

Yes! Pre-classifying routers are going to result in a lot of bad work because routing is hard and tend to underestimate the value of intelligence on many problems. OpenAI learned this with GPT-5, now

You really need to benchmark models for your use case. As soon as judgements & decisions stack on top of each other, the differences between…

model-releasesethan-mollick--x

You really need to benchmark models for your use case. As soon as judgements & decisions stack on top of each other, the differences between models amplifies, and no standard benchmark will tell you t

Z-1: Efficient Reinforcement Learning for Vision-Language-Action Models

arXiv:2606.31846v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models offer a promising framework for robotic manipulation by connecting language instructions, visual observations, and

3D Scene-Adaptive Trajectory-Controllable Human Image Animation with Camera Movement

arXiv:2606.30514v1 Announce Type: new Abstract: Human image animation, which aims to generate a video of a reference subject following a provided action sequence, has received increasing research inte

A Bayesian latent Gaussian process framework for aerodynamic uncertainty quantification

arXiv:2606.28871v1 Announce Type: cross Abstract: Predicting the aerodynamic performance (e.g. lift, drag, and moment coefficients) of an aircraft is challenging -- computational models are biased and

A Comparative Study on Affective Cues in Text Embeddings Across Psychological Emotion Theories

arXiv:2606.29068v1 Announce Type: cross Abstract: Text encoders are known for their utility in natural language processing, as they are able to efficiently compress inputs into dense vectors while pre

A Diagnostic Framework and Multi-Evaluator Audit of Evaluator-Driven Preference Dynamics in Self-Adapting LLM Agents

arXiv:2606.29719v1 Announce Type: cross Abstract: Measurements of proprietary LLM evaluators can become invalid within weeks -- we document one case and provide the diagnostic framework to detect it.

A Machine-Verified Proof of a Quantum-Optimization Conjecture

arXiv:2606.29687v1 Announce Type: cross Abstract: We report a machine-verified resolution of a problem open for over a decade in quantum optimization: the Farhi, Goldstone and Gutmann (FGG) conjecture

A multi-architecture study of specificity refinement and false-positive mechanism analysis in prostate MRI

arXiv:2606.29977v1 Announce Type: cross Abstract: Objectives: To characterize residual false positives in prostate MRI detection, and to evaluate a lightweight post-hoc refinement head for case-level

A Multi-Dataset Benchmark for Evaluating LLM Agents in Microservice Failure Diagnosis

arXiv:2606.29193v1 Announce Type: cross Abstract: LLM-based agents are reshaping microservice operations into AgentOps, where benchmarks are key to evaluating failure diagnosis over multimodal observa

A Physics-Grounded Benchmark for Multi-Agent Dynamics in World Models

arXiv:2606.28757v1 Announce Type: new Abstract: Generative world models hold immense promise as scalable simulators for autonomous systems, particularly for synthesizing rare but safety-critical multi

A Probabilistic Approach to Trajectory-Based Optimal Experimental Design

arXiv:2601.11473v2 Announce Type: replace-cross Abstract: We present a novel probabilistic approach for optimal experimental path design. In this approach a discrete path optimization problem is defin

A Stochastic--Geometric Theory of Scaling Laws in Grokking

arXiv:2606.30388v1 Announce Type: cross Abstract: Delayed generalization (ie~grokking) refers to the phenomenon in which a neural network fits its training data early in training but only begins to ge

Accelerating Q-learning through Efficient Value-Sharing across Actions

arXiv:2606.29806v1 Announce Type: cross Abstract: Action-values are foundational to many control algorithms such as Q-learning. Therefore learning action-values efficiently is central to reinforcement

Accelerating scientific discovery with Co-Scientist

arXiv:2502.18864v2 Announce Type: replace Abstract: Scientific discovery is driven by scientists generating novel hypotheses for complex problems that undergo rigorous experimental validation. To augm

Adaptive Financial Transformer with Regime-Gated Attention for Stock Return Prediction

arXiv:2606.29347v1 Announce Type: cross Abstract: Adaptive Financial Transformer (AFT) is proposed for stock return prediction under non-stationary financial markets. The model incorporates a Market R

ADEPT: An Entropy-Driven Dual-Strategy Agent for Interactive Video Retrieval

arXiv:2606.28326v1 Announce Type: cross Abstract: This research aims to solve the challenge of video retrieval from massive datasets, caused by ambiguous user queries. Prevailing single-round retrieva

AerialMetric: Benchmarking and Adapting UAV Monocular Metric Depth Estimation in the Real World

arXiv:2606.29716v1 Announce Type: new Abstract: This paper addresses the problem of monocular metric depth estimation in aerial UAV imagery. Although recent data-driven methods have achieved remarkabl

AERIS: Aerial-Edge Role-Driven Intelligence at Runtime via Orchestrated Language-Model Swarm

model-releasesarxiv-cs-ro

arXiv:2606.30151v1 Announce Type: new Abstract: Integrating large language models into robotic systems holds promise for enhancing autonomy, yet practical deployment remains constrained by strict hear

Agent-Computer Observation Interfaces Enable Dynamic Computer Use

arXiv:2606.29472v1 Announce Type: new Abstract: SWE-agent established the action interface as an underexplored design axis for software-engineering agents; we make the analogous case for the observati

Agentic Abstention: Do Agents Know When to Stop Instead of Act?

arXiv:2606.28733v1 Announce Type: new Abstract: LLM agents are expected to act over multiple turns, using search, browsing interfaces, and terminal tools to complete user goals. Yet not every goal is

Agile Reinforcement Learning through Separable Neural Architecture and Applications

arXiv:2601.23225v2 Announce Type: replace-cross Abstract: Deep reinforcement learning (RL) is increasingly deployed in resource-constrained environments, yet go-to function approximators - multilayer

Alternative Graph Neural Networks: Synergizing GEV Models and Deep Learning for Travel Mode Choice Modeling

arXiv:2509.07123v2 Announce Type: replace-cross Abstract: Generalized extreme value models capture dependence among choice alternatives in discrete choice modeling, but require this dependence to be p

An Agentic AI Pipeline for Appliance-Level Energy Anomaly Detection and LLM-Driven Recommendations

arXiv:2606.28467v1 Announce Type: cross Abstract: Appliance-level energy monitoring in office buildings produces noisy alerts that non-expert facility managers struggle to use. This paper proposes an

An AI agent for treatment reasoning over a biomedical tool universe

arXiv:2606.28692v1 Announce Type: new Abstract: Treatment reasoning underpins every therapeutic decision, integrating disease context, comorbidities, medications, contraindications, and evolving biome

Analysis of Adam Algorithms for Stochastic Dynamic Systems

arXiv:2606.28879v1 Announce Type: new Abstract: The adaptive moment estimation algorithm, known as Adam, is widely used in modern machine learning, owing to its low per-iteration complexity and strong

Analysis of Parameter Settings for the Bat Algorithm Using Variance Evolution

arXiv:2606.28644v1 Announce Type: cross Abstract: Parameter settings in evolutionary algorithms and metaheuristics are important because such parameter values can influence the performance of algorith

Animation2Code: Evaluating Temporal Visual Reasoning in Video-to-Code Generation

arXiv:2606.28593v1 Announce Type: cross Abstract: While recent vision-language models (VLMs) have achieved significant improvements on static visual-to-code tasks such as generating code for webpages,

Anisotropy Decides Cosine vs. Rank Metrics for Text Embeddings

arXiv:2606.29571v1 Announce Type: new Abstract: The standard way to compare two text embeddings is cosine similarity. Scattered studies report that a different metric does better, but never pin down t

Anthropic integration with Modal brings scalable compute to Claude Science

Anthropic has integrated Claude with Modal's serverless compute platform, enabling scalable cloud infrastructure for scientific computing workflows. This integration allows Claude to leverage Modal's

model-releasesmodal-blog

Anthropic launches Claude Science, an AI workbench that uses existing Claude models like Opus 4.8 to integrate 60+ scientific databases and specialized toolkits (Rebecca Bellan/TechCrunch)

Rebecca Bellan / TechCrunch: Anthropic launches Claude Science, an AI workbench that uses existing Claude models like Opus 4.8 to integrate 60+ scientific databases and specialized toolkits — Anthropi

Anthropic launches Claude Sonnet 5, saying it nears Opus 4.8 performance at lower prices and is substantially better than Sonnet 4.6 for agentic work (Anthropic)

Anthropic: Anthropic launches Claude Sonnet 5, saying it nears Opus 4.8 performance at lower prices and is substantially better than Sonnet 4.6 for agentic work — Claude Sonnet 5 is built to be the mo

Anthropic says the Department of Commerce has lifted export controls on Claude Fable 5 and Mythos 5 and that it will begin restoring access Wednesday (@anthropicai)

@anthropicai: Anthropic says the Department of Commerce has lifted export controls on Claude Fable 5 and Mythos 5 and that it will begin restoring access Wednesday — We've received notice that the Dep

Anthropic’s long-sidelined Fable 5 is greenlit to return

model-releasesthe-verge-ai

After weeks of negotiating with the Trump administration, Anthropic is finally going to be able to bring Claude Fable 5 back online. In a post on X, Anthropic said it plans to begin restoring access W

Anti-Collapse Dynamics and the Emergence of Multi-Time-Scale Learning in Recurrent Neural Networks

arXiv:2606.29519v1 Announce Type: new Abstract: Long-range learning is hard for recurrent networks trained with stochastic gradient descent, because the influence of a past input fades with the lag el

Argus: Metric Panoramic 3D Reconstruction for Indoor Scenes

arXiv:2606.30047v1 Announce Type: new Abstract: Metric feed-forward 3D reconstruction for panoramic data remains under-explored due to the lack of large-scale panoramic RGB-D training data. We present

Arko-T: A Foundation Model for Text-to-Structured 3D Generation

arXiv:2606.30429v1 Announce Type: new Abstract: Text-to-3D systems can now synthesize a mechanical part from a single sentence, yet the result is a shape to render, not a design to edit. We present Ar

ARMOR: Adaptive Retriever Optimization for Low-Resource Telecom Question Answering

arXiv:2606.29706v1 Announce Type: cross Abstract: Telecom question answering (QA) is a challenging setting for retrieval-augmented generation (RAG): evidence is fragmented across standards, papers, en

Assessing the Business Process Modeling Competences of Large Language Models

arXiv:2601.21787v2 Announce Type: replace-cross Abstract: The creation of Business Process Model and Notation (BPMN) models is a complex and time-consuming task requiring both domain knowledge and pro

Attractor States Emerge in Multi-Turn LLM Conversations

arXiv:2606.30571v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in open-ended multi-agent settings, but the long-run dynamics of model--model interaction remain po

Attribution Graphs and Causal Probing for Mechanistic Discovery and Bias Repair in Multimodal Generative Learning

arXiv:2510.12957v4 Announce Type: replace-cross Abstract: We treat the internals of generative models as mechanistic objects rather than black boxes. We introduce extbf{Attribution Graphs} (AGs), whic

Audio-Visual Continual Test-Time Adaptation without Forgetting

arXiv:2602.18528v2 Announce Type: replace Abstract: Audio-visual continual test-time adaptation involves continually adapting a source audio-visual model at test-time, to unlabeled non-stationary doma

AURORA: Asymmetry and Update-Induced Rotation for Robust Hallucination Detection in Large Language Models

arXiv:2606.29545v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities across a wide range of natural language processing tasks. However, their tendency

AWS launches an internal organization for AI-focused forward-deployed engineers, backed by $1B in resources, following OpenAI and others in launching FDE teams (Russell Brandom/TechCrunch)

Russell Brandom / TechCrunch: AWS launches an internal organization for AI-focused forward-deployed engineers, backed by $1B in resources, following OpenAI and others in launching FDE teams — As compa

AWS launches forward-deployed engineering team to speed enterprise agentic AI adoption

model-releasessiliconangle

Amazon Web Services Inc. said today it’s rolling out a new dedicated organization to bring agentic artificial intelligence systems, built on the same technology, to customers by embedding engineers in

BaRA: Bayesian Adaptive Rank Allocation for Parameter-Efficient Fine-Tuning

arXiv:2606.29184v1 Announce Type: new Abstract: While Low-rank adaptation (LoRA) enables highly efficient fine-tuning by constraining task-specific updates to fixed low-rank subspaces, this rigid desi