Search: “models”

The Sentence Transformers v5.4 update introduces first-class multimodal support, enabling the same familiar API to encode and compare texts, images, audio, and videos using both `SentenceTransforme...

toolshugging-face

9 Apr 2026

Human

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Refiant raises $5M to refine AI models with ‘nature-inspired’ energy efficiency

DGX agent

Artificial intelligence model compression startup Refiant AI said today it has raised $5 million in seed funding from VoLo Earth Ventures to try to put an end to the “arms race” that has ignited a mul

industrysiliconangle

9 Apr 2026

Tools

Pelicans for Meta's new Muse Spark models - plus I did a bit of a deep dive into the Code Interpreter and fascinating 'container.visual_grou…

Pelicans for Meta's new Muse Spark models - plus I did a bit of a deep dive into the Code Interpreter and fascinating 'container.visual_grounding' tools in their http://meta.ai chat UI https://simonwi

toolssimon-willison--x

8 Apr 2026

Model Releases

Gemma 4 31B brings dense multimodal reasoning to Together AI. Try Now: http://www.together.ai/models/gemma-4-31b

model-releasestogether-ai--x

Google's Gemma 4 31B is a dense multimodal model from Google DeepMind now available on Together AI's serverless infrastructure via the endpoint `google/gemma-4-31B-it`. It features a 256K context ...

9 Apr 2026

A Phenomenology of Neural Geometry in Vision-Language-Action Models

arXiv:2610.20840v1 Announce Type: cross Abstract: Robotic manipulation is inherently geometric, but what shape does the world take inside the policy that performs it? Prior work on vision-language-act

Condition-Contrastive Extrapolation for On-Policy Distillation of Language Models

arXiv:2610.21195v1 Announce Type: new Abstract: On-policy distillation (OPD) improves a student language model by training on its own generated trajectories with supervision from a stronger teacher. H

Tutorials

Do VLAs Really Follow Instructions? Diagnosing How-Level Instruction Following in Vision-Language-Action Models

arXiv:2610.21251v1 Announce Type: new Abstract: Vision-language-action (VLA) models are expected to follow instructions like their language backbones, yet prior work has focused on What-level instruct

tutorialsarxiv-cs-cv

ETH: Data-Balanced Heterogeneous Pipeline Parallelism for Training Large Models

arXiv:2610.22035v1 Announce Type: cross Abstract: Current heterogeneity-aware training systems for large models balance workloads by assigning unequal numbers of layers across pipeline stages, a strat

FastVLA: Task-Conditioned and Temporally Adaptive Visual Token Compression for Efficient Vision-Language-Action Models

arXiv:2610.22146v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models present a promising paradigm for general-purpose robot manipulation, but closed-loop deployment is often limited by

researcharxiv-cs-ro

Tutorials

Multi-Dimensional Featurizers Yield Fine-Grained Steering and Data Shaping in Robot Foundation Models

arXiv:2610.20767v1 Announce Type: new Abstract: Can better feature discovery improve control over robot behavior through internal interventions and training data? Recent work in vision and language mo

tutorialsarxiv-cs-ro

ReState: Noise-Level-Aware State Correction for Training-Free Object Removal in Few-Step Diffusion Models

arXiv:2610.21287v1 Announce Type: new Abstract: Training-free object removal commonly redirects self-attention away from the target region, but on few-step distilled diffusion models this often leaves

When to Ask for Help: A Decision-Theoretic Account and Measurement Standard for Slow-Module Scheduling in Dual-System Vision-Language-Action Models

arXiv:2610.21160v1 Announce Type: new Abstract: Dual-system vision-language-action (VLA) models pair a high-frequency fast policy with a slow, expensive module, and published trigger mechanisms for in

safetyarxiv-cs-ro

Applications

Complementary Future Token Pruning for World Action Models

arXiv:2610.19957v1 Announce Type: new Abstract: World action models (WAMs) jointly predict future visual states and robot actions, but processing dense future-frame tokens incurs substantial inference

applicationsarxiv-cs-ro

Large Language Models Extend Known Research But Do Not Create New Research Directions

arXiv:2610.17439v1 Announce Type: new Abstract: The success of autonomous research systems relies on the quality of the scientific hypotheses they generate. Recent studies report that human reviewers

agentsarxiv-cs-ai

Learning Adaptive Deliberation Control for Reliable Recognition with Multi-Agent Language Models

arXiv:2610.17840v1 Announce Type: new Abstract: Multi-agent deliberation can improve recognition by criticizing and revising candidate answers, but fixed controls cannot respond to changes in disagree

Outcome-Routed Distillation and Reinforcement Learning for Diffusion Language Models

arXiv:2610.19271v1 Announce Type: new Abstract: On-policy distillation provides dense supervision on the student's own samples, but its targets still come from the teacher. Verifier reinforcement lear

PROSE: Training-Free Egocentric Scene Registration with Vision-Language Models

arXiv:2606.16569v2 Announce Type: replace Abstract: Registering two captures of the same indoor space taken at different times underpins persistent spatial memory for robots and AR systems, yet the re

Radioactive Feedback: Tracing Models Trained by Label-Only LLM Supervision

arXiv:2610.15685v1 Announce Type: new Abstract: Conventional distillation transfers capability through teacher-generated demonstrations. LLM-as-a-Judge knowledge distillation offers a distinct and inc

Tree-Structured Synergy of Large Language Models and Bayesian Optimization for Efficient CASH

arXiv:2601.12355v3 Announce Type: replace Abstract: To lower the expertise barrier in machine learning, the AutoML community has focused on the CASH problem, which jointly automates algorithm selectio

ACCRUE: Continual Off-Policy Reinforcement Learning for Robot Foundation Models

arXiv:2610.18596v1 Announce Type: cross Abstract: Reinforcement learning (RL) post-training improves robot foundation models (RFMs) beyond their demonstrations, but real-world deployment demands more:

Assessing the Performance of AI Models in Misinformation Detection Using Predefined Social Noise Constructs

arXiv:2610.17469v1 Announce Type: new Abstract: Social media platforms generate vast volumes of user-generated content that often obscure meaningful discourse, a phenomenon conceptualized as social no

ByteMark: A Unified Byte-Level Watermark for Detection Across Language Models

arXiv:2610.14427v1 Announce Type: cross Abstract: As watermarking of LLM-generated text enters deployment, users increasingly need to check text whose source is unknown. Existing detectors read the wa

Constrained Diffusion Models with Primal-Dual Inference

arXiv:2606.17192v2 Announce Type: replace Abstract: This paper develops constrained diffusion models with primal-dual inference (PDI) to sample from optimal distributions of entropy-regularized optimi

CoPlanVLM: Coordinated Path Planning for a Robot Team using Vision Language Models

arXiv:2610.14341v1 Announce Type: new Abstract: We present CoPlanVLM, which uses a Vision Language Model (VLM) to translate a single natural-language instruction and image into coordinated paths for a

researcharxiv-cs-ro

Declarative Reactive Robot Behaviors from Imperative Language Models

arXiv:2610.17083v1 Announce Type: new Abstract: Large Language Models (LLMs) are predominantly trained on imperative programming languages, and existing work on LLM-based robot programming reflects th

agentsarxiv-cs-ro

Explainable Visual Anomaly Detection via Concept Bottleneck Models

arXiv:2511.20088v3 Announce Type: replace Abstract: In recent years, VAD (Visual Anomaly Detection) has attracted significant attention due to its high interpretability, as it provides visual explanat

GeoMotionGPT: Geometry-Aligned Motion Understanding with Large Language Models

arXiv:2601.07632v5 Announce Type: replace Abstract: Discrete motion tokenization has recently enabled Large Language Models (LLMs) to serve as versatile backbones for motion understanding and motion-l

safetyarxiv-cs-cv

Google DeepMind and Google Cloud plan to provide up to 200 European scientific researchers with access to their frontier AI models and $3M in compute credits (Foo Yun Chee/Reuters)

Foo Yun Chee / Reuters: Google DeepMind and Google Cloud plan to provide up to 200 European scientific researchers with access to their frontier AI models and $3M in compute credits — Google DeepMind

industrytechmeme

HaloBlock: Faster and Better Decoding for Diffusion Large Language Models

arXiv:2610.17948v1 Announce Type: new Abstract: Diffusion large language models (dLLMs) have attracted increasing research attention due to their bidirectional attention and arbitrary order decoding.

Harmonic Security, which uses small language models to inspect employee interactions with AI tools, raised a 50M Series B, taking its total funding to 76M (Duncan Riley/SiliconANGLE)

Duncan Riley / SiliconANGLE: Harmonic Security, which uses small language models to inspect employee interactions with AI tools, raised a 50M Series B, taking its total funding to 76M — Workplace arti

industrytechmeme

On the Dynamics of Delayed Generalization in Linear Models

arXiv:2602.08302v2 Announce Type: replace Abstract: Delayed generalization, where training accuracy becomes nearly perfect substantially before test accuracy, has often been studied in the context of

Physics Foundation Models for Efficient Control of Fluid Flows

arXiv:2610.15173v1 Announce Type: cross Abstract: We investigate whether a physics foundation model (PFM) pretrained for PDE forecasting can be repurposed for closed-loop fluid-flow control. We constr

TacitVLA: Reasoning Vision-Language-Action Models Without Reasoning Latency

arXiv:2610.17540v1 Announce Type: cross Abstract: Textual reasoning before acting has improved vision-language-action (VLA) models, but at the cost of latency: every action conditioned on the reasonin

agentsarxiv-cs-ro

Teacher-Guided Tool Learning for Small Language Models via Bidirectional KL Constraints

arXiv:2610.18459v1 Announce Type: new Abstract: External tools can extend the capabilities of small language models (SLMs), enabling their deployment in resource constrained environments. However, the

Test-Time Compute for Humanoid Behavior Foundation Models

arXiv:2610.14896v1 Announce Type: new Abstract: Humanoid Behavior Foundation Models (BFMs) can execute impressive motions, but downstream applications such as loco-manipulation demand high whole-body

researcharxiv-cs-ro

Training-Free Dense Hand Contact Estimation with Multi-Modal Large Language Models

arXiv:2605.05886v2 Announce Type: replace Abstract: Dense hand contact estimation requires both high-level semantic understanding and fine-grained geometric reasoning of human interaction to accuratel

Understanding the Interplay between Memorization and Learning in Large Language Models

arXiv:2507.14777v2 Announce Type: replace Abstract: We investigate foundational questions about the interplay between memorization and learning in large language models (LLMs). When an LLM generates a

Disentangling Total-Variance and Signal-to-Noise-Ratio Improves Diffusion Models

arXiv:2502.08598v3 Announce Type: replace Abstract: Diffusion models have been widely adopted as a powerful generative framework across numerous scientific domains, yet their inherently iterative samp

Leading Chinese mathematicians launch an alliance, including eight orgs and aiming for 1,000+ scientists, to focus on developing specialized AI models for math (Chao Kong/South China Morning Post)

Chao Kong / South China Morning Post: Leading Chinese mathematicians launch an alliance, including eight orgs and aiming for 1,000+ scientists, to focus on developing specialized AI models for math —

industrytechmeme

Neural expectation-maximization and meta-models

arXiv:2610.12741v1 Announce Type: new Abstract: We interpret Transformer networks as learned approximations to a hybrid probabilistic-inference procedure that combines max-product Loopy Belief Propaga

Understanding Transformer-based Vision Models through Inversion

arXiv:2412.06534v5 Announce Type: replace-cross Abstract: Understanding the internal mechanisms of deep neural networks remains a central challenge in machine learning. In computer vision, one promisi

A PDE Perspective on Generative Diffusion Models

arXiv:2511.05940v3 Announce Type: replace-cross Abstract: Score-based diffusion models have emerged as a powerful class of generative methods, with successful applications across diverse domains. Desp

ExecVLA: Following Fine-Grained Execution Constraints in Vision-Language-Action Models with Bi-Level Action Representation

arXiv:2603.17524v2 Announce Type: replace-cross Abstract: We study fine-grained execution-constraint following in vision-language-action (VLA) models. Given an invariant task goal, the policy must fol

Imperative Interference: Social Register Shapes Instruction Topology in Large Language Models

arXiv:2603.25015v2 Announce Type: replace-cross Abstract: System prompt instructions that cooperate in English compete in Spanish, with the same semantic content, but opposite interaction topology. We

Applications

Learned Image Compression for Vision-Language-Action Models

arXiv:2606.16253v2 Announce Type: replace-cross Abstract: Vision-language-action (VLA) models increasingly rely on high-frequency multi-camera observations, making visual communication a major bottlen

applicationsarxiv-cs-ai

Tutorials

Omni-Diffusion-Distill: Few-Step Distillation of Unified Multimodal Diffusion Large Language Models

arXiv:2610.10990v1 Announce Type: new Abstract: Unified multimodal diffusion large language models (dLLMs) offer a single architecture for both image generation and multimodal understanding, but their

tutorialsarxiv-cs-cv

Rethinking the Tradeoff Between Temporal Encoding and Nonlinear Computation in Spiking Language Models

arXiv:2610.10933v1 Announce Type: cross Abstract: Spiking language models face a tradeoff between representing continuous semantic features over short temporal windows and retaining costly nonlinear a

Skill-SLM: Agent Skill-driven Small Language Models for Reliable Robot Operation

arXiv:2610.10812v1 Announce Type: new Abstract: Small language models (SLMs) have been increasingly adopted for onboard robot operation because they enable intelligent decision-making. However, existi

agentsarxiv-cs-ro