Search: “models”

BioMatrix: Towards a Comprehensive Biological Foundation Model Spanning the Modality Matrix of Sequences, Structures, and Language

arXiv:2606.22138v1 Announce Type: cross Abstract: We present BioMatrix, the first multimodal foundation model that natively integrates sequences, structures, and natural language for both molecules an

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Black-Box Continual Learning for Vision-Language Models

DGX agent

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

model-releasesarxiv-cs-cv

23 Jun 2026

Decoupling the Declarative from the Procedural in Vision-Language-Action Models

arXiv:2606.21496v1 Announce Type: cross Abstract: Deploying generalist robotic agents in the real world requires transferable skills. Specifically, a policy trained to clone a behavior from object-spe

Discrete State Diffusion Models: A Sample Complexity Perspective

arXiv:2510.10854v3 Announce Type: replace Abstract: Diffusion models have demonstrated remarkable performance in generating high-dimensional samples across domains such as vision, language, and the sc

Distributional Regression with Tabular Foundation Models: Evaluating Probabilistic Predictions via Proper Scoring Rules

arXiv:2603.08206v5 Announce Type: replace Abstract: Modern tabular foundation models such as TabPFN and TabICL naturally produce full predictive distributions, while the benchmarks used to evaluate th

Do Activation Monitors Survive Model Updates? Benchmarking, Predicting, and Repairing Activation-Monitor Staleness

arXiv:2606.15980v2 Announce Type: replace Abstract: Activation monitors -- lightweight probes trained on a language model's internal representations -- are an increasingly common layer in deployment s

safetyarxiv-cs-lg

Interleaved Speech Language Models Latently Work In Text

arXiv:2606.22473v1 Announce Type: cross Abstract: Speech language models (SLMs) have been extensively studied, with the common paradigm incorporating text data and pre-trained text LMs. A leading appr

IOI: Decoupling Kinematics and Physics for Interactive World Models

model-releasesarxiv-cs-ro

arXiv:2606.23296v1 Announce Type: new Abstract: Developing generalist embodied agents requires interactive environments providing visually realistic feedback and accurate action-conditioned dynamics.

Learning a Normal World Model for Few-Shot Boundary-Calibrated Abnormality Detection

arXiv:2606.22261v1 Announce Type: new Abstract: Abnormality detection in complex systems faces two practical barriers: abnormal labels are scarce, and binary labels do not quantify how far an event ha

Localizing and Editing Knowledge in Large Audio-Language Models

arXiv:2603.14343v2 Announce Type: replace Abstract: Large Audio-Language Models (LALMs) have shown strong performance in speech understanding, making speech a natural interface for accessing factual i

MEDLAYXPLAIN: Benchmarking the Expert-Lay Gap in Medical Vision-Language Models

arXiv:2606.21194v1 Announce Type: new Abstract: Medical Vision-Language Models (Med-VLMs) achieve strong expert-level performance, yet their ability to generate patient-accessible descriptions remains

Applications

NAC: Neural Action Codec for Vision-Language-Action Models

arXiv:2606.21372v1 Announce Type: cross Abstract: Vision-language-action (VLA) models rely on discrete action tokenizers to bridge continuous robot control and autoregressive sequence modeling, yet ex

applicationsarxiv-cs-lg

On the Expressive Power of Weight Quantization in Large Language Models

arXiv:2606.22249v1 Announce Type: new Abstract: In recent years, weight quantization that encodes the learnable parameters of large language models in an n-bit format has garnered significant attentio

Local Ai

Perturbation-Based Uncertainty for Failure Detection in Vision-Language-Action Models

arXiv:2606.20754v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have shown strong performance in robotic manipulation, but reliable uncertainty quantification remains challenging,

local-aiarxiv-cs-ro

Policy4OOD: A Knowledge-Guided World Model for Policy Intervention Simulation against the Opioid Overdose Crisis

arXiv:2602.12373v2 Announce Type: replace Abstract: The opioid epidemic remains one of the most severe public health crises in the United States, yet evaluating policy interventions before implementat

rumors of new models being delayed

model-releasesgary-marcus--x

rumors of new models being delayed 🚨 SCOOP(s): - GPT-5.6 has been delayed and will no longer release this week. New target is ~mid-July. - DeepMind are not satisfied with the current state of 3.5 Pro

SafeDojo: Safe Reinforcement Learning for VLA via Interactive World Model

arXiv:2606.20698v1 Announce Type: new Abstract: Safe control is a prerequisite for real-world embodied intelligence, for which safe reinforcement learning has emerged as a promising paradigm. However,

safetyarxiv-cs-ro

Self-Evolving Cognitive Framework via Causal World Modeling for Embodied Scientific Intelligence

arXiv:2606.22449v1 Announce Type: cross Abstract: Current embodied world models are primarily optimized for predictive objectives, limiting their ability to generalize under distribution shifts and re

researcharxiv-cs-ro

Applications

SkyJEPA: Learning Long-Horizon World Models for Zero-Shot Sim-to-Real Control of Quadrotors

arXiv:2606.23444v1 Announce Type: cross Abstract: Accurate dynamics models are critical for informed decision-making in robotic systems, particularly for agile aerial vehicles operating under uncertai

applicationsarxiv-cs-lg

SVD-Surgeon: Optimal Singular-Value Surgery for Large Language Model Compression

arXiv:2606.23568v1 Announce Type: new Abstract: Large language models (LLMs) achieve remarkable performance across a wide range of tasks, but their deployment is constrained by substantial memory and

Temper-Then-Tilt: Principled Unlearning for Generative Models through Tempering and Classifier Guidance

arXiv:2602.10217v2 Announce Type: replace Abstract: We study machine unlearning in large generative models by framing the task as density ratio estimation to a target distribution rather than supervis

The Energy Consumption of Transformer Fine-Tuning: A Roofline-Inspired Scaling Model

arXiv:2606.23546v1 Announce Type: new Abstract: Transformer-based models underpin modern natural language processing but incur rapidly growing computational and energy costs. As training scales in bot

Agents

VDAWorld: World Modelling via VLM-Directed Abstraction and Simulation

arXiv:2512.11061v2 Announce Type: replace Abstract: Generative video models, a leading approach to world modelling, face fundamental limitations. They often violate physical and logical rules, lack in

agentsarxiv-cs-cv

Vera: A Layered Diffusion Model for Content-Preserving Video Editing

arXiv:2606.23610v1 Announce Type: new Abstract: Video diffusion models have enabled remarkable progress in video generation and editing. However, content preservation remains a core challenge: existin

Local Ai

What Shapes Emergent Misalignment? Insights from Training Dynamics, Model Priors, and Data

arXiv:2606.20814v1 Announce Type: cross Abstract: Emergent misalignment (EM) is a phenomenon in which models generalize with narrow fine-tuning, leading to broad (yet uneven) misalignment across evalu

local-aiarxiv-cs-lg

GLM-5.2 has been the most popular new model on Fireworks this past week. @ArtificialAnlys confirms why: #3 overall on GDPval-AA (1524 Elo), …

model-releasesfireworks-ai--x

GLM-5.2 has been the most popular new model on Fireworks this past week. @ArtificialAnlys confirms why: #3 overall on GDPval-AA (1524 Elo), #1 open weights by 116 points. Interest is showing no signs

In a rare joint statement, Five Eyes leaders warn AI models capable of taking down governments and businesses are mere months away, urging leaders to 'act now' (Sarah Basford Canales/The Guardian)

Sarah Basford Canales / The Guardian: In a rare joint statement, Five Eyes leaders warn AI models capable of taking down governments and businesses are mere months away, urging leaders to “act now” —

model-releasestechmeme

OpenAI unveils an updated GPT-5.5-Cyber model, launches the Patch the Planet initiative in partnership with Trail of Bits to fix open source bugs, and more (Lily Hay Newman/Wired)

Lily Hay Newman / Wired: OpenAI unveils an updated GPT-5.5-Cyber model, launches the Patch the Planet initiative in partnership with Trail of Bits to fix open source bugs, and more — Amid concerns abo

model-releasestechmeme

Three announcements from our keynote at Compile, including how we're training a new model with SpaceX.

Cursor announced three major initiatives at the Compile keynote, including a partnership with SpaceX to train a new AI model. The announcement highlights Cursor's expansion efforts and collaboration w

model-releasescursor--x

I released a softmax-free attention model at GPT-2 Medium scale (~354M params, 11.5B tokens): structural sparsity + tile-skipping kernels for long-context VRAM savings. Open weights + custom Triton kernels [R]

model-releasesr-machinelearning

A researcher released an open-source softmax-free attention model at GPT-2 Medium scale (354M parameters trained on 11.5B tokens) that uses structural sparsity and tile-skipping kernels to reduce VRAM

21 Jun 2026

4DP-QA: Scalable QA for 4D Perception in Vision Language Models

arXiv:2606.11568v1 Announce Type: new Abstract: Despite recent advances, Vision Language Models (VLMs) still struggle to grasp the dynamics of the world. We note that the ability to reason about a 4D

APEX: A Network-Native Time-Series Foundation Model for Forecasting and Anomaly Detection for Wireless Edge Operations

arXiv:2606.11553v1 Announce Type: new Abstract: Generic time-series foundation models transfer poorly to wireless network telemetry whose signals are bursty, zero-inflated, and coupled across protocol

Benchmarking Large Language Models for Safety Data Extraction

arXiv:2606.11204v1 Announce Type: new Abstract: Accurate extraction of structured information from Safety Data Sheets (SDS) remains challenging in industrial safety due to heterogeneous document forma

GLACIER: A Multimodal Student-Teacher Foundation Model for Molecular Property Prediction

arXiv:2606.11382v1 Announce Type: new Abstract: Deep learning models facilitate the discovery of molecules with tailored properties among billions of candidate compounds. However, the computational bu

safetyarxiv-cs-lg

Intermittent time series forecasting: local vs global models

arXiv:2601.14031v2 Announce Type: replace-cross Abstract: Forecasting intermittent time series, which contain zeros, is a crucial challenge in supply chains as inventory policies require probabilistic

safetyarxiv-cs-lg

LifeSentence: Language models can encode human life course trajectories from longitudinal panel data

arXiv:2606.11220v1 Announce Type: new Abstract: Forecasting human life outcomes is important to gain insights into how individuals attain long and healthy lives. Conventional statistical approaches yi

Modelling magnetic material properties with uncertainty-aware neural networks

arXiv:2606.11870v1 Announce Type: cross Abstract: Machine learning is increasingly applied to accelerate the discovery of novel materials by exploring large compositional and structural design spaces.

Ouroboros-Spatial: Closing the Data-Model Loop for Spatial Reasoning

arXiv:2606.11719v1 Announce Type: cross Abstract: Spatial reasoning remains a persistent challenge for multimodal large language models (MLLMs). Existing approaches largely rely on large-scale, static

researcharxiv-cs-ai

PLUME: Probabilistic Latent Unified World Modeling and Parameter Estimation for Multi-Finger Manipulation

model-releasesarxiv-cs-ro

arXiv:2606.11396v1 Announce Type: new Abstract: Dexterous manipulation with multi-finger hands can be sensitive to physical parameters such as object shape, pose, and friction coefficients. While simu

RAIL: Rethinking Auditory Intelligence in Large Audio-Language Models with a CHC-Grounded Benchmark

arXiv:2606.11260v1 Announce Type: cross Abstract: Humans process rich auditory environments through tightly integrated cognitive capabilities such as audio perception, audio reasoning, and memory. Des

WorldReasoner: Evaluating Whether Language Model Agents Forecast Events with Valid Reasoning

arXiv:2606.11816v1 Announce Type: cross Abstract: Forecasting real-world events requires language-model agents to reason under uncertainty from incomplete, time-bounded information. Yet evaluating whe

Anthropic backtracks on a policy limiting Claude Fable 5's ability to develop other AI models, after significant backlash from the AI research community (Maxwell Zeff/Wired)

Maxwell Zeff / Wired: Anthropic backtracks on a policy limiting Claude Fable 5's ability to develop other AI models, after significant backlash from the AI research community — The company changed cou

model-releasestechmeme

Cohere Transcribe, our open-source speech recognition model, is #1 on the new @huggingface Far-Field ASR benchmark.

Cohere has released Transcribe, an open-source speech recognition model that achieved the top ranking on Hugging Face's newly established Far-Field Automatic Speech Recognition (ASR) benchmark. The mo

model-releasescohere--x

Deployment-Time Memorization in Foundation-Model Agents

arXiv:2606.10062v1 Announce Type: new Abstract: Foundation-model agents are increasingly long-lived systems that remember users across interactions, making memorization an explicit deployment-time fun

Applications

Does Normalization Choice Matter for Causal Large Time-Series Models?

arXiv:2606.09954v1 Announce Type: cross Abstract: Large models for time-series forecasting have been emerged as a promising paradigm for training models on heterogeneous collections of signals. These

applicationsarxiv-cs-ai

Earth-OneVision: Extending Remote Sensing Multimodal Large Language Models to More Sensor Modalities and Tasks

arXiv:2606.10819v1 Announce Type: cross Abstract: RS-MLLMs enable natural-language understanding and spatial reasoning over earth observation imagery. However, existing models support only a narrow ra

From Observation to Intervention: A Causal Audit of Expert Importance in Mixture-of-Experts Models

arXiv:2606.10703v1 Announce Type: cross Abstract: Interpretability methods routinely use population-level summary statistics over observed model behaviour to license claims about the effects of target

KCSAT-ML: Probing Reasoning Models with Nationwide-Cohort Human Difficulty

arXiv:2606.10403v1 Announce Type: new Abstract: Math reasoning benchmarks have proliferated, yet most lack a per-item difficulty signal grounded in actual human performance. We introduce KCSAT-ML, a d