Search: “model-releases”

HAT-4D: Lifting Monocular Video for 4D Multi-Object Interactions via Human-Agent Collaboration

arXiv:2606.28215v1 Announce Type: cross Abstract: Extracting dynamic 4D object interactions from massive, in-the-wild monocular videos offers a highly efficient data collection pathway for scaling Emb

Model Releases

Health-ORSC-Bench: A Benchmark for Measuring Over-Refusal and Safety Completion in Health Context

DGX agent

arXiv:2601.17642v2 Announce Type: replace Abstract: Safety alignment in Large Language Models is critical for healthcare; however, reliance on binary refusal boundaries often results in over-refusal o

model-releasesarxiv-cs-ai

29 Jun 2026

HumanMoveVQA: Can Video MLLMs reason about human movement in videos?

arXiv:2606.27999v1 Announce Type: new Abstract: Despite the rapid advance of Multimodal Large Language Models (MLLMs) in high-level video understanding, a fundamental bottleneck remains: these models

Hybrid Fact-Checking that Integrates Knowledge Graphs, Large Language Models, and Search-Based Retrieval Agents Improves Interpretable Claim Verification

arXiv:2511.03217v2 Announce Type: replace-cross Abstract: Large language models (LLMs) excel in generating fluent utterances but can lack reliable grounding in verified information. At the same time,

Hyperellipsoid Density Sampling: Exploitative Sequences to Accelerate High-Dimensional Optimization

arXiv:2511.07836v4 Announce Type: replace-cross Abstract: The curse of dimensionality remains a persistent challenge in modern optimization problems. Expanding the search space into higher dimensions

iCost: A Novel Instance-Complexity-Based Cost-Sensitive Learning Framework

arXiv:2409.13007v3 Announce Type: replace-cross Abstract: Class imbalance poses a significant challenge in classification tasks, often causing standard learning algorithms to become biased toward the

In the next version of Claude Code: subagents run in the background by default, so you can keep talking to Claude while your subagents work …

model-releasesboris-cherny--x

In the next version of Claude Code: subagents run in the background by default, so you can keep talking to Claude while your subagents work If you want your agent to run in the foreground, just tell C

Internal documents: Meta is placing strict limits on how engineers in its applied AI division can use Claude Code and Codex, fearing inadvertent distillation (Jyoti Mann/The Information)

Jyoti Mann / The Information: Internal documents: Meta is placing strict limits on how engineers in its applied AI division can use Claude Code and Codex, fearing inadvertent distillation — As Meta Pl

model-releasestechmeme

Introducing Cloak: Use Claude or ChatGPT without your personal data ever leaving your machine. Two 3B models do the on-device PII cloaking: …

model-releasesemad-mostaque--x

Introducing Cloak: Use Claude or ChatGPT without your personal data ever leaving your machine. Two 3B models do the on-device PII cloaking: praxis-spanfinder-3b and praxis-relevance-3b. They swap your

June Launches | Desktop, MCP & Core Engine Improvements — Live Demo & Q&A https://x.com/i/broadcasts/1aJbddORnaoKX

ComfyUI announced June product launches featuring desktop application improvements, MCP (Model Context Protocol) enhancements, and core engine upgrades during a live demonstration with audience Q&A se

model-releasescomfyui--x

Ko-WideSearch: A Korean Breadth-Search Benchmark for Exhaustive Set Enumeration by Web Agents

model-releasesarxiv-cs-cl

arXiv:2606.27595v1 Announce Type: new Abstract: Web-agent benchmarks overwhelmingly measure depth -- pinning one obscure answer behind a chain of constraints -- while breadth, exhaustively enumerating

Lawmakers want to ban AI companies from selling your health data

model-releasesthe-verge-ai

A new proposal would ban the sale of Americans' health and location information to data brokers - including information people reveal to an AI chatbot like ChatGPT or Claude. In the coming weeks, Sena

Learning in Markovian bandits with non-observable states and constrained decision epochs

arXiv:2606.27448v1 Announce Type: new Abstract: This paper studies the problem of regret minimization in Markovian bandits with non-observable states and possibly constrained decision epochs. The focu

Learning Peer Influence Probabilities with Linear Contextual Bandits

arXiv:2510.19119v2 Announce Type: replace Abstract: In networked environments, it is common for users to share recommendations about content, products, services, and possible courses of action. Whethe

Learning to Evict from Key-Value Cache

model-releasesarxiv-cs-cl

arXiv:2602.10238v2 Announce Type: replace Abstract: The growing size of Large Language Models (LLMs) makes efficient inference challenging, primarily due to the memory demands of the autoregressive Ke

LLawCo: Learning Laws of Cooperation for Modeling Embodied Multi-Agent Behavior

arXiv:2606.28182v1 Announce Type: cross Abstract: Embodied agents operating in decentralized and partially observable environments have attracted growing attention in recent years. However, existing l

LocalNav: Distilling Frontier VLMs and Embodied RL for On-Device Object Goal Navigation

model-releasesarxiv-cs-ro

arXiv:2606.27871v1 Announce Type: new Abstract: Vision Language Models (VLMs) have emerged in the robotic domain as a powerful tool that enables environmental perception with language context, serving

Lost at the End: Primacy Bias in Multimodal Retrieval-Augmented Question Answering

arXiv:2606.16494v2 Announce Type: replace-cross Abstract: Knowledge-based visual question answering (KB-VQA) lets vision-language systems answer questions that exceed their parametric knowledge by con

Mapping Europe’s AI Workforce Opportunity

This OpenAI publication analyzes employment opportunities and workforce transitions related to artificial intelligence development and deployment across Europe. It likely examines which sectors and re

model-releasesopenai

MemoBench: Benchmarking World Modeling in Dynamically Changing Environments

arXiv:2606.27537v1 Announce Type: new Abstract: Video generation models aspire to simulate dynamic environments, and several benchmarks now evaluate memory consistency across frames. However, most ass

Mitigating LLM-based p-Hacking by Preregistering for the Next LLM

arXiv:2606.27687v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to generate, classify, and annotate data whose outputs feed downstream hypothesis tests. However, L

MLVC: Multi-platform Learned Video Codec for Real-World Deployment

arXiv:2606.28027v1 Announce Type: cross Abstract: Neural video codecs have surpassed classical codecs in coding efficiency but remain impractical for deployment due to cross-platform incompatibility a

MobileManiBench: Simplifying Model Verification for Mobile Manipulation

model-releasesarxiv-cs-ro

arXiv:2602.05233v2 Announce Type: replace Abstract: Vision-language-action models have advanced robotic manipulation but remain constrained by reliance on the large, teleoperation-collected datasets d

Monocular Avatar Reconstruction via Cascaded Diffusion Priors and UV-Space Differentiable Shading

arXiv:2606.28144v1 Announce Type: new Abstract: Reconstructing high-fidelity, relightable 3D avatars from a single in-the-wild image is a challenging ill-posed problem, primarily hindered by the scarc

Monte Carlo with kernel-based Gibbs measures: Guarantees for probabilistic herding

arXiv:2402.11736v3 Announce Type: replace Abstract: Kernel herding belongs to a family of deterministic quadratures that seek to minimize the maximum mean discrepancy (MMD), that is, the worst-case in

Mosaic: A Benchmark Suite for Differentiable Physics Solvers

arXiv:2606.27895v1 Announce Type: cross Abstract: Differentiable partial differential equation (PDE) solvers underpin solver-in-the-loop ML training, gradient-based optimal control, and inverse proble

Most popular model on @OpenRouter (10tr tokens) turns out to be a 1.6tr MoE by @Meituan_LongCat (superapp/DoorDash of China) Basically Gemin…

model-releasesemad-mostaque--x

Most popular model on @OpenRouter (10tr tokens) turns out to be a 1.6tr MoE by @Meituan_LongCat (superapp/DoorDash of China) Basically Gemini / Opus 4.6 level 35tr tokens trained entirely on 50k Chine

MultiHashFormer: Hash-based Generative Language Models

arXiv:2606.28057v1 Announce Type: cross Abstract: Language models (LMs) represent tokens using embedding matrices that scale linearly with the vocabulary size. To constrain the parameter footprint, pr

Multimodal Evaluator Preference Collapse: Cross-Modal Coupling in Self-Evolving Agents

model-releasesarxiv-cs-cl

arXiv:2606.16682v3 Announce Type: replace-cross Abstract: When AI agents use language models to evaluate their own outputs in a feedback loop, systematic biases emerge. We show that Evaluator Preferen

MVPruner: Dynamic Token Pruning for Accelerating Multi-view Vision-Language Models in Autonomous Driving

arXiv:2606.27660v1 Announce Type: new Abstract: Vision-Language Models (VLMs) improve generalization and interpretability in autonomous driving but suffer from efficiency issues due to long visual tok

NormAct: A Benchmark for Hidden Social Norm Compliance in Embodied Planning

arXiv:2606.27826v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) are increasingly deployed as embodied planners in egocentric environments, where task success requires not only

Not All Relations Rotate Alike: Transformation-Aware Decoupling for Viewpoint-Robust 3D Scene Graph Generation

arXiv:2606.27412v1 Announce Type: cross Abstract: 3D Scene Graph Generation (3DSGG) represents 3D scenes as structured object-relation-object graphs, providing a compact relational abstraction for spa

Open Models, Closed Environments: Palantir Brings Secure AI to US Agencies With NVIDIA Nemotron

model-releasesnvidia-blog

Showcasing the importance of open source innovation in American AI, Palantir’s new intelligent engine — introduced today — uses NVIDIA Nemotron open models to serve the needs of U.S. government agenci

Operator Learning for Cubic Nonlinear Schrodinger Equation on Periodic Domains

arXiv:2606.27459v1 Announce Type: new Abstract: We consider the cubic nonlinear Schrodinger (NLS) equation on two-dimensional flat tori with varying aspect ratios. In this formulation, the choice of a

Ornith-1.0: Self-Scaffolding LLMs for Agentic Coding

model-releasessimon-willison

Ornith-1.0: Self-Scaffolding LLMs for Agentic Coding This is an interesting new open weights (MIT licensed) model, the first model release from DeepReinforce. [...] with variants including 9B Dense, 3

OrthoTryOn: Geometric Orthogonalization for Conflict-Free Unified Fashion Generation

arXiv:2606.27880v1 Announce Type: new Abstract: Unified fashion generation integrates tasks like virtual try-on and garment reconstruction into a single model to reduce task-specific adaptation costs.

Output-Space Allocation Costs for Calibration-Guided LLM Compression: An Empirical Study

arXiv:2606.27785v1 Announce Type: cross Abstract: Training-free compression methods for large language models (LLMs) often use calibration data to guide compression decisions. ROCKET, a recent method

Pair Nova 2 Lite with Claude for cost-optimized document processing

model-releasesaws-ml-blog

In this post, we show how pairing Amazon Nova 2 Lite with Anthropic’s Claude Sonnet 4.6 delivers an efficient solution for digitizing scanned documents at scale. We built a two-model pipeline on Amazo

Parameter-Efficient Continuous-Variable Photonic Quantum Neural Networks for Edge Quantum AI: Demonstration in Oral Cancer Detection

arXiv:2606.28252v1 Announce Type: cross Abstract: Early detection of oral cancer markedly improves clinical outcomes, yet specialized diagnostic tools remain scarce in low-resource settings. Smartphon

Parameter Efficient Hybrid Transformer (PEHT) for Network Traffic Prediction via Dynamic Urban Congestion Integration

arXiv:2606.28274v1 Announce Type: cross Abstract: Accurate network traffic prediction is a critical element for efficient resource allocation in dynamic urban cellular networks. However, prediction re

Parameter-Efficient Quantum-Inspired Fast Weight Programmers for Traffic-Matrix Forecasting

arXiv:2606.27821v1 Announce Type: cross Abstract: Traffic matrices (TMs) capture network-wide origin-destination demand and are central to traffic engineering, yet accurate whole-matrix forecasting re

PEBS: Per-rater Empirical-Bayes Shrinkage for RLHF Reward-Model Calibration

arXiv:2606.27578v1 Announce Type: cross Abstract: Reward models for Reinforcement Learning from Human Feedback (RLHF) pool preferences across thousands of annotators and fit one global affine calibrat

PerceptionRubrics: Calibrating Multimodal Evaluation to Human Perception

arXiv:2606.28322v1 Announce Type: new Abstract: We introduce PerceptionRubrics, a rubric-based evaluation framework that addresses the gap between saturated benchmark scores and real-world brittleness

Position Bias Correction is Insufficient for One-Pass Attention Sorting

arXiv:2606.27793v1 Announce Type: cross Abstract: Long-context language models suffer from position bias, where information in middle positions is underutilized. Attention Sorting addresses this by it

Prism Transformer: Progressive Head Schedules for Hierarchical Attention Processing

arXiv:2606.27449v1 Announce Type: new Abstract: Multi-head attention conventionally partitions the hidden dimension equally across all heads at every layer, enforcing an identical representational sub

ProactiveBench: Benchmarking Proactiveness in Multimodal Large Language Models

arXiv:2603.19466v2 Announce Type: replace Abstract: Effective collaboration begins with knowing when to ask for help. For example, when trying to identify an occluded object, a human would ask someone

QuantV2X: A Fully Quantized Multi-Agent System for Cooperative Perception

arXiv:2509.03704v2 Announce Type: replace Abstract: Cooperative perception through Vehicle-to-Everything (V2X) communication offers significant potential for enhancing vehicle perception by mitigating

Qwen-Image-2.0-RL Technical Report

arXiv:2606.27608v1 Announce Type: new Abstract: We present Qwen-Image-2.0-RL, a post-training pipeline that applies reinforcement learning from human feedback (RLHF) and on-policy distillation (OPD) t