Search: “model-releases”

ACE-GS: Acing the Trade-off with Accurate, Compact and Efficient 3D Gaussian Splatting

arXiv:2606.21244v1 Announce Type: new Abstract: 3D Gaussian Splatting achieves exceptional real-time rendering, but its substantial computational and storage demands hinder widespread deployment. Exis

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Model Releases

Achieving widetilde{O}(1/epsilon) Sample Complexity for Bilinear Systems Identification under Bounded Noises

DGX agent

arXiv:2603.20819v2 Announce Type: replace Abstract: This paper studies finite-sample set-membership identification for discrete-time bilinear systems under bounded symmetric log-concave disturbances.

model-releasesarxiv-cs-lg

23 Jun 2026

AD-Bench: A Real-World, Trajectory-Aware Advertising Analytics Benchmark for LLM Agents

arXiv:2602.14257v2 Announce Type: replace-cross Abstract: While Large Language Model (LLM) agents have made remarkable progress on complex reasoning, evaluating them in real-world environments remains

Adam Converges in Nonsmooth Nonconvex Optimization

arXiv:2606.22326v1 Announce Type: cross Abstract: Adam is one of the most widely implemented and influential modern optimizers. Why is it effective across different optimization problems in practice?

Adam symmetry theorem: characterization of the convergence of the stochastic Adam optimizer

arXiv:2511.06675v2 Announce Type: replace-cross Abstract: Beside the standard stochastic gradient descent (SGD) method, the Adam optimizer due to Kingma & Ba (2014) is currently probably the best-know

AEF-Econ: Toward Plug-and-Play Socioeconomic Foundation Embeddings from AlphaEarth for Urban Remote Sensing

arXiv:2606.20697v1 Announce Type: new Abstract: AlphaEarth Foundations (AEF) unify global remote sensing foundation embeddings through multimodal self-supervised learning, but their pretraining focuse

AgentMisalignment: Measuring the Propensity for Misaligned Behaviour in LLM-Based Agents

arXiv:2506.04018v3 Announce Type: replace-cross Abstract: As Large Language Model (LLM) agents become more widespread, associated misalignment risks increase. While prior research has studied agents'

AI Agents Can Already Autonomously Perform Experimental High Energy Physics

arXiv:2603.20179v3 Announce Type: replace-cross Abstract: Large language model-based AI agents are now able to autonomously execute substantial portions of a high energy physics (HEP) analysis pipelin

An agentic loop (compile, test, profile, revise) helps. Gemini 3 Pro went from 24 to 35/87 correct, then plateaued after ~20 steps. Feedback…

model-releasestogether-ai--x

An agentic loop (compile, test, profile, revise) helps. Gemini 3 Pro went from 24 to 35/87 correct, then plateaued after ~20 steps. Feedback fixes syntax, not rank coordination, collective ordering, o

... and now you can buy your own! https://happy-pelicans.printify.me/product/29480311 Proceeds go to http://birdrescue.org, a local non-prof…

model-releasessimon-willison--x

... and now you can buy your own! https://happy-pelicans.printify.me/product/29480311 Proceeds go to http://birdrescue.org, a local non-profit that rescues pelicans (among other birds) I printed a cus

Anthropic launches Claude Tag, an agentic AI coworker for Slack that can learn context, give suggestions, and more, in beta for Claude Team and Enterprise tiers (David Gewirtz/ZDNET)

David Gewirtz / ZDNET: Anthropic launches Claude Tag, an agentic AI coworker for Slack that can learn context, give suggestions, and more, in beta for Claude Team and Enterprise tiers — ZDNET's key ta

model-releasestechmeme

Anticipating the Optimism Gap: Predicting Distribution-Shift Degradation of RF-Impairment Detectors from In-Distribution Statistics

arXiv:2606.22054v1 Announce Type: cross Abstract: Detectors for GNSS radio-frequency impairments (jamming, spoofing, multipath) are usually reported with a single AUC measured on the distribution they

ASCII Art Turns LLMs into VLA Controllers

arXiv:2606.21470v1 Announce Type: cross Abstract: Vision--Language--Action (VLA) controllers are often built by extending vision--language models (VLMs) with action supervision, relying on multimodal

Assistron: Bayesian Shared Autonomy with Off-the-shelf Vision-Language-Action Models

model-releasesarxiv-cs-ro

arXiv:2606.23147v1 Announce Type: new Abstract: We propose Assistron, a shared autonomy model that leverages Vision-Language-Action (VLA) models to assist the user in daily activities. Our approach is

Atomistic Language Models Understand and Generate Materials

arXiv:2606.21395v1 Announce Type: new Abstract: Atomistic structure and natural language have long been modeled separately, with language models either calling atomistic models as tools or being fine-

Attacking the Trusted Imagination: Oracle-Level Integrity Attacks on Imagine-then-Act World Models

arXiv:2606.22966v1 Announce Type: new Abstract: Many recent vision-language-action (VLA) policies adopt an imagine-then-act design. A world-action model (WAM) first imagines a short future as a latent

AutoDex: An Automated Real-World System for Dexterous Grasping Data Collection

arXiv:2606.23689v1 Announce Type: cross Abstract: Learning robust dexterous grasping requires real-world data that records the physical outcomes of grasp attempts. Such data is hard to obtain at scale

Available today: the API, Document AI in Mistral AI Studio, Amazon SageMaker, Microsoft Foundry, coming soon Snowflake Parse Document, or se…

model-releasesmistral-ai--x

Available today: the API, Document AI in Mistral AI Studio, Amazon SageMaker, Microsoft Foundry, coming soon Snowflake Parse Document, or self-hosted on a single container, so your documents never lea

Bayesian Adaptation Gym: A Benchmark for the Bayesian Low-Rank Adaptation of Multi-Modal Language Models

arXiv:2606.22188v1 Announce Type: new Abstract: Large multi-modal language models are increasingly deployed in high-stakes domains, making well-calibrated uncertainty essential. Traditional Bayesian m

BELDE: Building a Large-scale Earth-observation Land-cover Dataset for Europe

arXiv:2606.20909v1 Announce Type: new Abstract: Earth observation imagery plays a critical role in environmental monitoring, urban planning, disaster assessment, and climate analysis. While multi-spec

BELLS-O: Evaluating the Operational Trade-offs of LLM Supervision Systems

arXiv:2606.20668v1 Announce Type: cross Abstract: LLM supervision systems, namely input/output moderation filters and jailbreak detectors, are the primary safeguard against misuse in deployed AI appli

Benchmarking Robot Memory Under Interference

arXiv:2606.22338v1 Announce Type: cross Abstract: Robots deployed in realistic settings will accumulate experience across many sessions and tasks over their deployment. The robot's tasks may often req

Benchmarking Vision-Language Models for Microscopic Plant Image Understanding

arXiv:2606.22497v1 Announce Type: new Abstract: Microscopic imaging provides essential visual evidence for studying plant biology and pathology at the cellular and subcellular levels. However, existin

Beyond Accuracy: Measuring Bias Acknowledgment in Chain-of-Thought Reasoning for Responsible AI Evaluation

arXiv:2606.15127v2 Announce Type: replace Abstract: Reasoning models are increasingly used in settings where the final answer is not the only object of review: educational tools may show students inte

Beyond Fixed Budgets: Characterizing the Inelasticity and Limitations of Tree-of-Thought Reasoning Strategies

arXiv:2606.20599v1 Announce Type: cross Abstract: Tree of Thought (ToT) search has become a promising direction for improving the reasoning capabilities of large language models, but deploying these m

Beyond 'One Language, One Script': Quantifying Orthographic Bias in Multilingual VLMs with PuMVR

arXiv:2606.20770v1 Announce Type: cross Abstract: Current Vision-Language Models (VLMs) are celebrated for their multilingual capabilities, yet they operate under a flawed assumption: that one languag

Beyond the LUMIR challenge: The pathway to foundational registration models

arXiv:2505.24160v3 Announce Type: replace-cross Abstract: Medical image challenges have played a transformative role in advancing the field, catalyzing innovation and establishing new performance benc

BIFE: Better Interaction, Fewer Errors for Minute-Long Video Generation

arXiv:2511.22973v2 Announce Type: replace Abstract: Long video generation is a critical step toward building realistic world models, requiring both high visual fidelity and long-range interaction cons

Black-Box Continual Learning for Vision-Language Models

arXiv:2606.22999v1 Announce Type: new Abstract: The rapid deployment of Vision-Language Models (VLMs) in dynamic environments necessitates the ability to learn continuously without forgetting. However

BranchShine: Compact Raw-Audio-to-IPA Transcription with a RoPE E-Branchformer Encoder

arXiv:2606.22824v1 Announce Type: new Abstract: Speech-to-IPA transcription is useful when the desired output is pronunciation rather than orthographic text, but competitive multilingual systems are o

Bring open models to where you're already working. FireConnect brings Fireworks' top models directly into Claude Code, Pi, OpenCode, and Cod…

model-releasesfireworks-ai--x

Bring open models to where you're already working. FireConnect brings Fireworks' top models directly into Claude Code, Pi, OpenCode, and Codex. Watch our Head of AI Education @Prof_oz show you how: Ho

CAOA -- Completion-Assisted Object-CAD Alignment

arXiv:2606.18429v2 Announce Type: replace Abstract: Accurately aligning CAD models to their corresponding objects in indoor RGB-D scans is a central challenge in 3D semantic reconstruction. The task r

CapRiCorn-1K: A Comprehensive Benchmark for Video Captioning and Subject Referential Consistency Across Temporal Scales

arXiv:2606.21949v1 Announce Type: new Abstract: Accurate and comprehensive video captions with consistent subject references are critical for downstream understanding and generation tasks. However, fe

Catching Lies Without Sending the Video: Privacy-Preserving Multimodal Deception Detection

arXiv:2606.22699v1 Announce Type: new Abstract: Frontier multimodal models can guess whether a person is lying from a testimony video. To do so, they stream that raw face and voice to a third-party mo

CDER-SME: A Cross-Device Event-RGB Micro-Expression Dataset under Multi-Level Stress Induction

arXiv:2606.20715v1 Announce Type: new Abstract: Micro-expression recognition (MER) in realistic scenarios demands high temporal sensitivity and ecological validity, yet existing benchmarks are largely

CFAgentBench: A Reproducible Environment and Benchmark for Autonomous Construction-Finance Agents

arXiv:2606.22000v1 Announce Type: cross Abstract: We introduce CFAgentBench, a reproducible, self-hostable environment and benchmark for autonomous construction-finance agents: a CFO/controller-class

Chains That See, Answers That Don't: A Multi-Aspect Evaluation Recipe for Forced Chain-of-Thought on Video-MME

arXiv:2606.22862v1 Announce Type: new Abstract: Forced chain-of-thought (CoT) is widely assumed to make vision-language models more reliable on video question answering. We propose a small three-probe

Chehre: An Emoji-Prompted Video Dataset for Perceptually Diverse Facial Expression Recognition

arXiv:2606.21657v1 Announce Type: new Abstract: Facial expressions are nonverbal social signals used in human interaction, but facial expression recognition datasets often focus on static images, basi

Chem2Gen-Bench: Benchmarking Chemical-to-Genetic Translation in Perturbation Response Space

arXiv:2606.21109v1 Announce Type: new Abstract: Virtual-cell and perturbation models are increasingly used to predict cellular responses for biomedical discovery, but chemical and genetic perturbation

CheXpercept: A Benchmark for Evaluating Expert-Level Lesion Perception in Chest X-rays

arXiv:2606.21020v1 Announce Type: new Abstract: The evaluation of vision-language models (VLMs) for chest X-ray (CXR) analysis has largely been limited to disease-presence classification without visua

ChronoLock: Protecting Videos from Unauthorized Text-to-Video Personalization

arXiv:2606.21146v1 Announce Type: new Abstract: Text-to-video (T2V) diffusion models have made it increasingly easy to synthesize realistic and temporally coherent videos, while recent personalization

Claude is really proactive with Claude Tag. You don’t need to prompt it to do work, it can do work proactively based on your instructions. I…

model-releasesboris-cherny--x

Claude is really proactive with Claude Tag. You don’t need to prompt it to do work, it can do work proactively based on your instructions. It has excellent memory and access to your data, so it can be

Claude Tag is an incredible new form factor for agents, so I think it's going to take some time to figure out the best practices, but these …

Claude Tag is an incredible new form factor for agents, so I think it's going to take some time to figure out the best practices, but these are some of my favorites 🧵 Introducing Claude Tag, a new way

model-releasesthariq--x

Clipping the Price of Adaptivity at the Tail

arXiv:2606.22669v1 Announce Type: new Abstract: Adaptive stochastic convex optimization (SCO) methods face a fundamental ``price of adaptivity'' barrier: under the standard set of assumptions, they ca

Cluster-Specific Localized Drift Detection for Efficient Batch Model Adaptation under Controlled Distribution Shift

arXiv:2606.22026v1 Announce Type: new Abstract: Machine learning systems deployed in dynamic environments frequently operate under nonstationary data distributions, where controlled distribution shift

CodePercept: Code-Grounded Visual STEM Perception for MLLMs

arXiv:2603.10757v2 Announce Type: replace Abstract: When MLLMs fail at Science, Technology, Engineering, and Mathematics (STEM) visual reasoning, a fundamental question arises: is it due to perceptual

Comparative Evaluation of Machine Learning and Deep Learning Models for Wound-Rotor Synchronous Motor Performance Prediction

arXiv:2606.21230v1 Announce Type: new Abstract: Wound rotor synchronous motors have emerged as a strong alternative that eliminates dependence on REEs. However, WRSM design requires the simultaneous o

Concept-Constrained Prompt Learning for Few-Shot CLIP Adaptation

arXiv:2606.22567v1 Announce Type: new Abstract: Few-shot prompt learning is an effective strategy for adapting CLIP to downstream tasks, but class-only prompt optimization can overfit base-class super