Search: “models”

AgentGym2: Benchmarking Large Language Model Agents in De-Idealized Real-World Environments

arXiv:2607.05174v1 Announce Type: new Abstract: Language agents, i.e., LLM agents, progress rapidly and are increasingly deployed in production environments. This trend underscores the urgent need for

Research

AMT-APC: Automatic Piano Cover by Fine-Tuning an Automatic Music Transcription Model

DGX agent

arXiv:2409.14086v2 Announce Type: replace-cross Abstract: There have been several studies on automatically generating piano covers, and recent advancements in deep learning have enabled the creation o

researcharxiv-cs-lg

7 Jul 2026

APeB: Benchmarking Personalization Ability of Large Language Model Agents

arXiv:2607.03162v1 Announce Type: new Abstract: LLM-powered agents struggle with personalization when users issue raw, underspecified queries. In this setting, agents must infer latent intent, extract

Hardware

AquaGen: Scaling generative models to molecular dynamics precision on thousands of atoms

arXiv:2607.03513v1 Announce Type: cross Abstract: We present AquaGen, the first all-atom, explicit solvent, periodic-boundary-condition-aware generative model that produces molecular configurations fr

hardwarearxiv-cs-lg

CanniUplift: A Holistic Framework for Mitigating Seller and Incentive Cannibalization in E-commerce Uplift Modeling

arXiv:2607.05242v1 Announce Type: cross Abstract: Personalized incentive allocation is vital for e-commerce, where uplift modeling is the standard for estimating Individual Treatment Effects (ITE). Ho

safetyarxiv-cs-ai

EyeMulator: Improving Code Language Models by Mimicking Human Visual Attention

arXiv:2508.16771v3 Announce Type: replace-cross Abstract: Code Language Models (CodeLLMs) learn token importance from data correlations, whereas human developers attend selectively to semantically sal

tutorialsarxiv-cs-ai

Gemma 4 Technical Report

arXiv:2607.02770v1 Announce Type: cross Abstract: We introduce Gemma 4, a new generation of open-weight, natively multimodal language models in the Gemma model family. Designed to advance compute effi

GeoFlow: Geo-Aware Modeling of Inter-Area Relationships in Origin-Destination Flow Prediction and Generation

arXiv:2607.05257v1 Announce Type: new Abstract: Origin-destination (OD) flow modeling underpins urban planning and mobility analysis, but prevailing graph-based methods often neglect salient geographi

researcharxiv-cs-lg

Hierarchical Sparse Attention Done Right: Toward Infinite Context Modeling

arXiv:2607.02980v1 Announce Type: cross Abstract: Scaling modern large language models (LLMs) to long contexts is limited by the quadratic computation cost, and poor length extrapolation of dense atte

Tools

Hugging Face Models on Foundry Managed Compute

This article describes how to use Hugging Face models with Microsoft's Foundry Managed Compute infrastructure, likely covering integration steps, deployment options, and the benefits of running open-s

toolshugging-face

Applications

Labeled-Data-Free Meta-Learning: Efficient Task Generation Using Pre-trained Models and Unlabeled Data

arXiv:2607.02850v1 Announce Type: new Abstract: Meta-learning without labeled data is crucial for real-world applications, where obtaining labeled datasets can be expensive or restricted due to privac

applicationsarxiv-cs-lg

Language Models Represent and Transform Concepts with Shared Geometry

arXiv:2607.04525v1 Announce Type: cross Abstract: How concepts are represented in neural networks is a fundamental question in machine learning. The dominant view treats concept representations as sta

Latent Clarity: Bridging World-Model Kinematics to Semantic Manifolds for Video Anomaly Anticipation

arXiv:2607.03558v1 Announce Type: cross Abstract: Continuous video anomaly detection is dominated by reactive Multiple Instance Learning (MIL) that collapses spatiotemporal features into scalar scores

LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation

arXiv:2607.04270v1 Announce Type: cross Abstract: Large language models (LLMs) have recently emerged as powerful backbones for recommender systems by reformulating recommendation as a token-level gene

safetyarxiv-cs-ai

Look Before You Leap: Distilling Tree Search into Action Evaluation for Frozen VLA Models

arXiv:2607.03751v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models acquire broad embodied capabilities through large-scale pretraining, yet their generalization remains far more fragi

researcharxiv-cs-ro

Moonstone: A Multimodal Foundation Model and Benchmark for Lunar Remote Sensing

arXiv:2607.03644v1 Announce Type: cross Abstract: Decades of orbital missions have produced multi-modal remote sensing data for the Moon, spanning optical imagery, spectroscopy, thermal emission, rada

Optimizing Large Language Models for Causality Assessment in Pharmacovigilance: Developing a Performance Metric as Objective for Bayesian Hyperparameter Optimization

model-releasesarxiv-cs-cl

arXiv:2607.03704v1 Announce Type: new Abstract: Background: Growing individual case safety report (ICSR) volumes have intensified demand for scalable automated causality assessment. Large Language Mod

PRISM3D: Probabilistic Refinement and Robust Initialization for Physically Consistent Scene Modeling under Extreme Motion Blur

model-releasesarxiv-cs-cv

arXiv:2607.03855v1 Announce Type: new Abstract: We address the inverse problem of blind 3D scene reconstruction from extremely motion-blurred images, a scenario where traditional Structure-from-Motion

RLIE: Rule Generation with Logistic Regression, Iterative Refinement, and Evaluation for Large Language Models

arXiv:2510.19698v3 Announce Type: replace Abstract: Large Language Models (LLMs) can propose rules in natural language, sidestepping the need for a predefined predicate space in traditional rule learn

tutorialsarxiv-cs-ai

Robobench: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models as Embodied Brain

model-releasesarxiv-cs-cv

arXiv:2510.17801v2 Announce Type: replace-cross Abstract: Building robots that can perceive, reason, and act in dynamic, unstructured environments remains a central challenge. Recent embodied systems

RoboVista: Evaluating Vision Language Models for Diverse Robot Applications

model-releasesarxiv-cs-ro

arXiv:2607.04610v1 Announce Type: new Abstract: Diverse applications for robotics, such as industry and agriculture, require robots to operate across various embodiments, changing visual conditions, a

Tensor-Train Joint Modeling for Few-Step Discrete Diffusion

arXiv:2607.03788v1 Announce Type: new Abstract: Discrete diffusion promises orders-of-magnitude faster generation than autoregressive (AR) models for sequential discrete data, yet its full potential o

safetyarxiv-cs-lg

Token Communications: A Large Model-Driven Framework for Cross-modal Context-aware Semantic Communications

arXiv:2502.12096v5 Announce Type: replace-cross Abstract: In this paper, we introduce token communications (TokCom), a large model-driven framework to leverage cross-modal context information in gener

tutorialsarxiv-cs-cv

ToolFailBench: Diagnosing Tool-Use Failures in LLM Agents

arXiv:2607.04686v1 Announce Type: cross Abstract: Tool calling is central to modern language model agents, but aggregate benchmark scores often hide where tool use fails. A model that never calls a ne

TORINO: Token Reduction via Interpretable Concept Overlap in Vision-Language Models

arXiv:2607.04593v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have demonstrated impressive capabilities across different tasks, but their computational cost is dominated by the large

Toward Trustworthy Large Language Model Agents in Healthcare

arXiv:2607.05055v1 Announce Type: new Abstract: Healthcare appointment scheduling remains a persistent operational bottleneck, driven by manual coordination, fragmented legacy systems, and high admini

Towards transferable lightweight neuromorphic computing through a model-free temporal-switch framework

model-releasesarxiv-cs-lg

arXiv:2607.02608v1 Announce Type: cross Abstract: Lightweight neuromorphic computing offers a promising route to efficient AI, with particular benefits for resource-constrained edge deployments. Howev

Video Generation Models Are Inherent Lighting Estimators

arXiv:2607.04674v1 Announce Type: new Abstract: Recovering dynamic environment maps from a single in-the-wild video is crucial for photorealistic rendering, yet remains a challenge. Recent video gener

researcharxiv-cs-cv

Applications

Alex Karp, frontier models and the real fight for Enterprise AI

Palantir Technologies Inc. Chief Executive Alex Karp’s recent broadside against the frontier model vendors put a knife to the throat of the central enterprise artificial intelligence debate. Karp’s ar

applicationssiliconangle

5 Jul 2026

ACID: Action Consistency via Inverse Dynamics for Planning with World Models

arXiv:2607.02403v1 Announce Type: cross Abstract: Decision-time planning with action-conditioned world models has become a popular paradigm for embodied control. However, the standard planning cost ju

BALF: Budgeted Activation-Aware Low-Rank Factorization for Fine-Tuning-Free Model Compression

model-releasesarxiv-cs-lg

arXiv:2509.25136v3 Announce Type: replace Abstract: Activation-aware low-rank factorization techniques yield strong compression results but are generally confined to linear layers, while existing whit

Can Language Models Actually Retrieve In-Context? Drowning in Documents at Million Token Scale

arXiv:2607.01538v1 Announce Type: new Abstract: Language models (LMs) raise an intriguing alternative to vector-based retrieval: conditioning on an in-context corpus and directly generating a relevant

researcharxiv-cs-cl

ESC: Emotional Self-Correction for Reliable Vision-Language Models

arXiv:2607.02089v1 Announce Type: cross Abstract: Vision-language models (VLMs) have achieved strong performance across diverse multimodal tasks, yet they remain vulnerable to unreliable reasoning. Ex

safetyarxiv-cs-ai

Industry

First builds of Model Y Long Wheelbase at Giga Texas

Tesla has begun initial production of the Model Y Long Wheelbase variant at its Gigafactory Texas facility. The Long Wheelbase version offers extended interior space and cargo capacity compared to the

industryelon-musk--x

From Monolingual to Multilingual: Evaluating Mamba for ASR in South African Languages

model-releasesarxiv-cs-cl

arXiv:2607.01502v1 Announce Type: new Abstract: Recent advances in automatic speech recognition (ASR) have explored different sequence models, including Conformer-based models and newer state space mo

Agents

Language Models as Measurement Apparatus for Culture

arXiv:2607.02459v1 Announce Type: new Abstract: Language models are increasingly used to quantify cultural phenomena, but what makes such measurement distinctively cultural? This paper argues that NLP

agentsarxiv-cs-cl

Probing Chemical Language Models: Effects of Pre-training and Fine-tuning

arXiv:2607.02140v1 Announce Type: new Abstract: Chemical language models (CLMs) are trained with linearized representations such as SMILES, yet it remains unclear which chemically meaningful substruct

researcharxiv-cs-lg

Visually Grounded Self-Reflection for Vision-Language Models via Reinforcement Learning

arXiv:2607.02490v1 Announce Type: new Abstract: Large vision-language models can reason over multimodal inputs by generating textual chains of thought (CoT). A key capability exhibited in CoT reasonin

tutorialsarxiv-cs-cl

Local Ai

ABot-M0.5: Unified Mobility-and-Manipulation World Action Model

arXiv:2607.00678v1 Announce Type: new Abstract: Mobile manipulation is a key capability for general-purpose robots, yet remains challenging for current embodied learning methods. VLA policies are typi

local-aiarxiv-cs-cv

AI sovereignty isn’t optional. Don’t give away your alpha so easily. Protect it as much as you can. Open source models are critical and shou…

AI sovereignty isn’t optional. Don’t give away your alpha so easily. Protect it as much as you can. Open source models are critical and should be an important part of any individual’s, organisation’s,

researchdair-ai--x

But yikes does Fable write text that sounds like a parody of a Claude model on overdrive.

model-releasesethan-mollick--x

This post critiques Fable AI's text generation style, suggesting it produces overly verbose or exaggerated outputs that parody Claude's characteristic writing patterns taken to an extreme. The comment

CAT: Confidence-Adaptive Thinking for Efficient Reasoning of Large Reasoning Models

arXiv:2607.00862v1 Announce Type: cross Abstract: Large Reasoning Models (LRMs) have achieved remarkable success on complex tasks by leveraging long chain-of-thought (CoT) trajectories, yet they frequ

Characterizing and Identifying Separable Graphical Models

arXiv:2607.01057v1 Announce Type: cross Abstract: We study a broad class of graphical models whose independencies correspond to vertex separation in mixed graphs with directed, undirected, and bidirec

researcharxiv-cs-lg

Closed-loop coupling of personalised and foundation models for real-time treatment guidance with MRI

arXiv:2607.00500v1 Announce Type: cross Abstract: Image-guided therapies, including radiotherapy, biopsy and deep brain stimulation, rely on real-time targeting of anatomical structures. However, in t

researcharxiv-cs-cv

Cross-Domain Generalization Failure in Lightweight Intrusion Detection Models for IIoT Networks

arXiv:2607.00553v1 Announce Type: cross Abstract: Lightweight machine learning models are increasingly proposed for intrusion detection in Industrial Internet of Things (IIoT) networks due to their su

Entropy-Regularized Probabilistic Gates for Sparse Model Discovery in Scarce-Data Federated Learning

arXiv:2607.00275v1 Announce Type: cross Abstract: Federated Learning (FL) is a distributed machine learning (ML) paradigm with collaboration among multiple clients without sharing data. FL is challeng

Explainability in mulimodal deep transformation models for stroke outcome prediction

arXiv:2504.06299v2 Announce Type: replace-cross Abstract: Multimodal prediction models based on imaging and clinical data are increasingly used for clinical decision support, yet their interpretabilit

researcharxiv-cs-cv

Generative Model Proposal based Particle Filtering for Data Assimilation

arXiv:2607.01012v1 Announce Type: new Abstract: Data assimilation models state dynamics conditioned on sequential observations, and has wide-ranging scientific applications. In the filtering setting,

tutorialsarxiv-cs-lg