model releases

Grounding Sim-to-Real Generalization in Robotic Manipulation: An Empirical Study with Vision-Language-Action Models

arXiv:2603.22876v2 Announce Type: replace-cross Abstract: Learning a generalist control policy for robotic manipulation typically relies on large-scale datasets. Given the high cost of real-world data

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Hard-constraint physics-residual networks for hydrogen crossover prediction and high-pressure extrapolation in PEM water electrolysis

DGX agent

arXiv:2511.05879v5 Announce Type: replace-cross Abstract: Hydrogen crossover is a critical safety and efficiency constraint in high-pressure polymer electrolyte membrane water electrolysis (PEMWE), bu

model-releasesarxiv-cs-ai

30 Jun 2026

Have your agent record video demos of its work with shot-scraper video

model-releasessimon-willison

shot-scraper video is a new command introduced in today's shot-scraper 1.10 release which accepts a storyboard.yml file defining a routine to run against a web application and uses Playwright to recor

HEARTS: Benchmarking LLM Reasoning on Health Time Series

arXiv:2603.06638v3 Announce Type: replace-cross Abstract: The rise of large language models (LLMs) has shifted time series analysis from narrow analytics to general-purpose reasoning. Yet, existing be

Heterogeneous Tactile Transformer

model-releasesarxiv-cs-ro

arXiv:2606.29948v1 Announce Type: new Abstract: Tactile sensors are inherently heterogeneous: a model trained on one sensor cannot be directly used on another, which limits learning contact-rich manip

Hierarchical Experimentalist Agents

arXiv:2606.29315v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to take actions in the real world and support human decision-making, yet most agents rely on parametr

How AI settled the complexity of the oldest SGD algorithm

arXiv:2606.29593v1 Announce Type: cross Abstract: In 1937, Stefan Kaczmarz proposed a simple algorithm for solving systems of linear equations. This algorithm turned out to be the earliest known examp

How ChatGPT adoption has expanded

ChatGPT adoption has grown significantly since its launch, expanding across diverse user demographics, industries, and use cases globally. OpenAI's analysis likely covers metrics such as user growth,

model-releasesopenai

How Do LLMs Cite? A Mechanistic Interpretation of Attribution in Retrieval-Augmented Generation

arXiv:2606.28358v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) aims to enhance the trustworthiness of Large Language Models (LLMs) by grounding their outputs in external docume

How Far Can Sharpness and Complexity Jointly Explain Generalization?

arXiv:2606.29043v1 Announce Type: new Abstract: Sharpness and complexity are two central factors in the generalization analysis of deep neural networks. Existing quantitative evaluations of generaliza

How Far Can You Get Without a GPU? A Systematic Benchmark of Lightweight Hallucination Detection Across Question Answering, Dialogue, and Summarisation

arXiv:2606.29809v1 Announce Type: cross Abstract: Hallucination detection has become a pressing requirement for trustworthy AI deployment at scale. The most accurate detection methods depend on GPU-in

How Far Do On-Prem Open LLMs Get on Text-to-SQL? A Cross-Family Size x Technique Frontier on BIRD

arXiv:2606.29733v1 Announce Type: new Abstract: Organizations that cannot send data to a cloud API increasingly ask: how good is Text-to-SQL if the model must run on-premises on open weights, and whic

How LLMs See Creativity: Zero-Shot Scoring of Visual Creativity with Interpretable Reasoning

arXiv:2606.29672v1 Announce Type: new Abstract: Evaluating the originality of visual images poses enduring challenges for creativity assessment. Automated scoring using AI models has proven effective

How much of an LLM-generated clinical corpus is actually new? A production-scale measurement of content redundancy for provenance classification

arXiv:2606.29605v1 Announce Type: new Abstract: Clinical machine learning increasingly relies on training corpora generated by large language models (LLMs) rather than annotated by clinicians, and suc

How Schrödinger sped up molecular discovery by 4x with Alphaevolve

model-releasesgoogle-cloud-ai

Computational chemistry researchers have traditionally faced a frustrating trade-off when simulating molecular interactions: use fast classical force fields that sacrifice precision or rely on accurat

How to Train Your Long-Context Visual Document Model

arXiv:2602.15257v3 Announce Type: replace-cross Abstract: We present the first comprehensive, large-scale study of training long-context vision language models up to 344K context, targeting long-docum

HyBIRD: Hyperbolic Bridge Retrieval and Diagnosis for Methodology Inspiration Retrieval

arXiv:2606.28336v1 Announce Type: cross Abstract: Methodology Inspiration Retrieval (MIR) asks a system to retrieve prior papers whose methods can inspire a new research proposal. Unlike general scien

I-BBS: Coordinate-Free Inference of Latent Sub-Manifolds Using Random Distance Matrix Theory

arXiv:2606.29675v1 Announce Type: new Abstract: Bogomolny, Bohigas and Schmit (BBS) found that the spectrum of the pairwise distance matrix on N points sampled from a smooth d-dimensional manifold enc

IBRSteG: Learning a Generalizable Steganography Framework for 3D Gaussian Splatting

arXiv:2606.30024v1 Announce Type: cross Abstract: Recent advances in deep learning have notably improved steganographic message hiding. However, designing a generalizable steganographic approach for 3

IMCBench: A benchmark for multimodal LLMs in Image-grounded Medical Conversations

arXiv:2606.28556v1 Announce Type: new Abstract: Recent advances in large language models and vision-language models have enabled reasoning over multimodal data, offering opportunities for clinical app

Improved Predictive Performance and Interpretability for Mesomorphic Neural Networks Using Local Fidelity Regularization

arXiv:2606.29951v1 Announce Type: new Abstract: Interpretable Mesomorphic Neural Networks (IMNs) offer a promising framework that combines the predictive power of deep neural networks with the interpr

Improving Coherence in Hierarchical Time Series Forecasting using Structured Temporal Fusion

arXiv:2606.28553v1 Announce Type: new Abstract: In many real-world applications, such as retail sales, energy usage, and supply chain planning, forecasting is performed across hierarchical structures.

Inference chip startup Etched launches with $800M in funding

model-releasessiliconangle

Etched Inc., a developer of artificial intelligence inference chips, launched today with 800 million in funding. The startup raised the capital over multiple rounds. The most recent investment, which

Inside Genebench-Pro

Genebench-Pro appears to be a case study or tool from OpenAI focused on benchmarking or evaluating genetic/genomic analysis capabilities, likely demonstrating how OpenAI's models or tools can be appli

model-releasesopenai

Insidious by Design: Implications of Large Language Model algorithmic bias for the Global South

arXiv:2606.28333v1 Announce Type: cross Abstract: egin{quote} The biases in Large Language Models' (LLMs) outputs remain inadequately theorised, particularly from the perspective of the Global South.

Instance-Conditioned Adaptation for Large-scale Generalization of Neural Routing Solver

arXiv:2405.01906v3 Announce Type: replace Abstract: In modern intelligent transportation systems (ITS), particularly in freight transportation and logistics, real-time route planning is crucial. It pr

InterEdit: Navigating Text-Guided 3D Dyadic Human Motion Editing

arXiv:2603.13082v2 Announce Type: replace Abstract: Text-guided 3D motion editing has seen success in single-person scenarios, but its extension to multi-person settings is less explored due to limite

Intermediate Text Representation Guided Text-to-Image Generation for Enhancing One-and-Only Alignment

arXiv:2606.30262v1 Announce Type: new Abstract: Text-to-image (T2I) diffusion models often fail to faithfully render explicit textual descriptions, instead defaulting to strongly learned visual priors

Internal-State Probes Read the Situation, Not the Action: Three Negative Results for Pre-Action Misalignment Monitoring

arXiv:2606.30449v1 Announce Type: new Abstract: Probes on model internals could help monitor agentic systems if they identify harmful text or tool actions before those actions are generated. We ask wh

Internalized Reasoning for Long-Context Visual Document Understanding

arXiv:2604.02371v2 Announce Type: replace-cross Abstract: Visual long-document understanding is critical for enterprise, legal, and scientific applications, yet the best performing open recipes have n

Introducing Claude Sonnet 5 on AWS: Anthropic’s most capable Sonnet model

model-releasesaws-ml-blog

Today, we’re excited to announce the availability of Anthropic’s most advanced Sonnet model, Claude Sonnet 5, on Amazon Bedrock and Claude Platform on AWS. Claude Sonnet 5 is the first Sonnet model of

Introducing GeneBench-Pro

GeneBench-Pro is a comprehensive benchmarking tool or dataset introduced by OpenAI designed to evaluate AI model performance on genomic and gene-related tasks. It likely provides standardized metrics

model-releasesopenai

Introducing SWE-Together: a multi-turn benchmark built from real user–agent coding sessions. Coding agents are often benchmarked like exam-t…

model-releasesjeremy-howard--x

Introducing SWE-Together: a multi-turn benchmark built from real user–agent coding sessions. Coding agents are often benchmarked like exam-takers: given the full spec up front, then graded on the fina

It Lied to a Doctor to Buy Poison Ingredients: Quantifying Real-World Misuse of Phone-use Agents

arXiv:2606.27944v1 Announce Type: cross Abstract: Phone-use Agents can execute complex tasks end to end across real mobile applications. By operating a real device on the user's behalf, they reach far

JuZhou 1.0 Technical Report: The First Edge-Native Text-to-Image Foundation Model Trained Entirely on China-Developed AI Accelerators

arXiv:2606.28421v1 Announce Type: cross Abstract: Text-to-image (T2I) diffusion models typically require substantial computational resources and cloud infrastructure, posing significant challenges for

Know Before You Fetch: Calibrated Retrieval-Budget Allocation for Retrieval-Augmented Generation

arXiv:2606.29959v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) typically retrieves a fixed number of passages for every query. This is wasteful when the reader already knows th

KnowsTFM: Knowledge-Informed Fine-Tuning of Small Tabular Foundation Models

arXiv:2606.30258v1 Announce Type: cross Abstract: Tabular foundation models have advanced deep learning for tabular data by delivering strong default performance across many small and medium tasks. Ye

KrishokChat: A Citation-Grounded Dataset and Benchmark for Bengali Agricultural Advisory

arXiv:2606.29243v1 Announce Type: new Abstract: We present KrishokChat, the first citation-grounded Bengali agricultural instruction-tuning dataset for crop advisory in low-resource settings. We estab

Labeling Training Data for Entity Matching Using Large Language Models

arXiv:2606.28823v1 Announce Type: new Abstract: Recent large language models (LLMs) achieve strong performance on entity matching without requiring task-specific training data. However, applying these

LatSearch: Latent Reward-Guided Search for Faster Inference-Time Scaling in Video Diffusion

arXiv:2603.14526v2 Announce Type: replace Abstract: The recent success of inference-time scaling in large language models has inspired similar explorations in video diffusion. In particular, motivated

LaVPR: Benchmarking Language and Vision for Place Recognition

arXiv:2602.03253v2 Announce Type: replace Abstract: Visual Place Recognition (VPR) often fails under extreme environmental changes and perceptual aliasing. Beyond these limitations, standard systems c

Learning Cross-view Correspondences for Geo-localization on Planetary Surfaces

arXiv:2606.29821v1 Announce Type: new Abstract: Maintaining global position awareness is a fundamental challenge for planetary surface exploration, since satellite-based positioning systems are unavai

Learning from Reliable Latent Prompts for Visual Recognition with Missing Modalities

arXiv:2606.30597v1 Announce Type: new Abstract: Large-scale multimodal models (LMMs) have achieved superior performance in visual recognition by synergizing information across diverse, massive-scale p

Learning from samples: inverse problems over measures

arXiv:2505.07124v3 Announce Type: replace Abstract: We study inverse problems where an unknown potential is observed only through samples from the measure it induces by a convex variational principle.

Learning to Bid in Discriminatory Auctions with Budget Constraints

arXiv:2606.29252v1 Announce Type: new Abstract: We study repeated bidding in multi-unit discriminatory (pay-as-bid) auctions for a single bidder with per-round utility equal to value minus alpha times

Learning to Route and Schedule LLMs from User Retrials via Contextual Queueing Bandits

arXiv:2602.02061v2 Announce Type: replace Abstract: Explosive demands for LLMs often cause user queries to accumulate in server queues, requiring efficient routing (query-LLM matching) and scheduling

Learning to Segment Liquids in Real-world Images

arXiv:2601.00940v2 Announce Type: replace Abstract: Liquids like water, wine and medicine are everywhere. However, limited attention has been given to the task of segmenting liquids, hindering the abi

LEDGER: Scaling Agentic Document Editing with Dependency-aware Graph Retrieval

arXiv:2606.28379v1 Announce Type: cross Abstract: We introduce LEDGER to tackle the novel context engineering challenge of agentic document editing, where localized edits to long, structured documents