Search: “models”

LISA: Linear-Indexed Sparse Attention for Efficient Long-Context Reasoning

arXiv:2607.19358v1 Announce Type: new Abstract: Recent advances in long chain-of-thought reasoning models such as DeepSeek-R1 have led to increasingly longer inference context lengths under the test-t

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Memory-Augmented Multimodal Large Language Models for Small Object Understanding in Streaming Aerial Videos

DGX agent

arXiv:2607.19857v1 Announce Type: cross Abstract: Language-guided aerial perception aims to understand user-specified tiny targets in complex unmanned aerial vehicle (UAV) scenes. In real UAV deployme

researcharxiv-cs-ai

23 Jul 2026

Now We Know? A Systematic Comparison of TerraMind and THOR

arXiv:2607.18504v1 Announce Type: cross Abstract: Benchmarks for Geospatial Foundation Models (GFMs) increasingly rank models by aggregate score, but such rankings obscure why models differ: how much

researcharxiv-cs-cv

Rarity-Aware Discrete Diffusion with Spatially Consistent Decoding for Photo-Realistic Image Super-Resolution

model-releasesarxiv-cs-cv

arXiv:2607.17612v2 Announce Type: replace Abstract: Continuous diffusion models have become the dominant paradigm for photo-realistic image Super-Resolution (SR), but they typically formulate reconstr

Statistical Early Stopping for Reasoning Models

arXiv:2602.13935v2 Announce Type: replace Abstract: While LLMs have seen substantial improvement in reasoning capabilities, they also sometimes overthink, generating unnecessary reasoning steps, parti

Total Variation Distance Estimation in Autoregressive Models

arXiv:2607.19510v1 Announce Type: new Abstract: Modern LLM deployments use a number of implementation choices and inference optimizations (e.g., batching, custom kernels, and quantization) on top of f

researcharxiv-cs-lg

Zero-Shot Heart Rate Variability Forecasting from Consumer Wearables Using Time Series Foundation Models

arXiv:2607.20027v1 Announce Type: new Abstract: Short-term Heart Rate Variability (HRV) forecasting could provide clinicians with actionable lead time for detecting autonomic dysfunction and adverse c

local-aiarxiv-cs-lg

BREAKING: Kimi K3 by @Kimi_Moonshot is 1st overall on 3D Design with an Elo of 1450. This is a 6 position and 108 Elo jump from @Kimi_Moonsh…

model-releaseskimi-moonshot--x

BREAKING: Kimi K3 by @Kimi_Moonshot is 1st overall on 3D Design with an Elo of 1450. This is a 6 position and 108 Elo jump from @Kimi_Moonshot's previous model, Kimi K2.6. This performance puts Kimi K

21 Jul 2026

Tutorials

My book, Reinforcement Learning from Human Feedback is done! This is the book I wish I had when learning to fine-tune, align, & now post-tra…

My book, Reinforcement Learning from Human Feedback is done! This is the book I wish I had when learning to fine-tune, align, & now post-train models since ChatGPT. The resource has been built by me f

tutorialsswyx--x

21 Jul 2026

Sakana AI is doubling down on a thesis we believe will play an increasingly important role in AI development: the future of AI won't be defi…

model-releasesdavid-ha--x

Sakana AI is doubling down on a thesis we believe will play an increasingly important role in AI development: the future of AI won't be defined by a single frontier model, but by how intelligently man

21 Jul 2026

Accuracy Without Grounding: Diagnosing Visual Dependency Dissociation in Video LLM Benchmarks

arXiv:2607.13305v1 Announce Type: cross Abstract: Benchmark accuracy in video large language models (LLMs) is often treated as evidence of visual understanding. We audit this assumption across twenty

Baselines Before Architecture: Evaluating Coding Agents for Autonomous Penetration Testing

arXiv:2607.13085v1 Announce Type: cross Abstract: Recent autonomous penetration testing papers report high benchmark scores while adding multi-component security harnesses around frontier LLMs. Becaus

Cortical-SSM: A Deep State Space Model for Motor Imagery Decoding from EEG Signals

arXiv:2510.15371v2 Announce Type: replace-cross Abstract: Classification of electroencephalogram (EEG) signals obtained during motor imagery (MI) has substantial application potential, including commu

DeepCormack: Fermi surface tomography using model-based data-driven algorithms

arXiv:2607.13107v1 Announce Type: cross Abstract: The experimental reconstruction of the 3D two-photon momentum density (TPMD) via angular correlation of electron-positron annihilation radiation (ACAR

researcharxiv-cs-lg

Efficient and Privacy Aware Edge Cloud Collaborative Inference for Large Language Models

arXiv:2607.13093v1 Announce Type: cross Abstract: On-device LLM inference faces a trilemma of response latency, limited hardware resources and user privacy. Full cloud inference delivers strong comput

local-aiarxiv-cs-ai

Inference Economics of Enterprise Coding Agents: A Case Study of Cloud vs. On-Premise LLMs

arXiv:2607.13080v1 Announce Type: cross Abstract: Autonomous coding agents force engineering organizations to choose between API-based frontier models -- strong reasoning at high token cost -- and on-

M^ext{4}World: A Multi-view Multimodal Driving World Model for Interactive Object Manipulation and Minute-long Streaming

arXiv:2607.14005v1 Announce Type: new Abstract: Driving-world generation has emerged as a core capability for scalable autonomous-driving simulation, yet existing methods remain limited in object-leve

agentsarxiv-cs-cv

Microstructure-Conditioned Surrogate Models for Graded Multiscale Optimization of Mycelium Composites

arXiv:2607.13688v1 Announce Type: new Abstract: Emerging sustainable materials increasingly rely on engineered hierarchy and microstructure to achieve control of their properties and mechanical behavi

applicationsarxiv-cs-lg

Post-Disaster Affected Area Segmentation with a Vision Transformer (ViT)-based EVAP Model using Sentinel-2 and Formosat-5 Imagery

arXiv:2507.16849v3 Announce Type: replace-cross Abstract: We propose a vision transformer (ViT)-based deep learning framework to refine disaster-affected area segmentation from remote sensing imagery,

Towards Spatial Supersensing in the Wild

model-releasesarxiv-cs-cv

arXiv:2607.13681v1 Announce Type: new Abstract: Humans can efficiently parse continuous sensory streams, from hours to years, scaffolding an internal world model that grounds spatial reasoning and pre

Unleashing Multimodal Large Language Models for Training-free HOI Detection in the Wild

arXiv:2607.13881v1 Announce Type: cross Abstract: Human-object interaction detection (HOID) has traditionally been formulated as a supervised detection problem over predefined interaction categories.

agentsarxiv-cs-ai

v0.32.1

model-releasesollama-releases

What's Changed Improved Gemma 4 tool calling and multi-turn reasoning, including more reliable tool-response continuations Fixed a recurrent MLX model cache leak that could increase memory use across

A Shared Subcircuit Lets LLMs Count Down Across Tasks

model-releasesarxiv-cs-cl

arXiv:2607.12279v1 Announce Type: new Abstract: Writing a sentence of exactly twelve words; ending a DNA sequence at the right codon; formatting an ASCII table. These are all tasks that language model

Auditing Data Leakage in Whole-Slide Image Multimodal Benchmarks

model-releasesarxiv-cs-cv

arXiv:2607.12278v1 Announce Type: new Abstract: Recent vision-language models (VLMs) for computational pathology report striking zero-shot performance on whole-slide image (WSI) visual question answer

First, do NOHARM: a medical safety benchmark and randomized study of physician and AI teaming on clinical consultations

arXiv:2512.01241v4 Announce Type: replace-cross Abstract: Large language models (LLMs) and medical AI tools are routinely used by physicians and patients for medical advice, yet their clinical safety

Jetson-PI: Towards Onboard Real-Time Robot Control via Foresight-Aligned Asynchronous Inference

arXiv:2607.12659v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have achieved impressive performance on diverse embodied tasks. However, deploying VLA models on low-power onboard

Leveraging Prior Knowledge of Diffusion Model for Person Search

arXiv:2510.01841v2 Announce Type: replace Abstract: Person search aims to jointly perform person detection and re-identification by localizing and identifying a query person within a gallery of uncrop

local-aiarxiv-cs-cv

LIDAR-AD: A Decoder-Free Latent-Interaction Dreamer with Action-Residual Chains for Autonomous Driving

arXiv:2607.11964v1 Announce Type: new Abstract: Autonomous driving requires long-horizon closedloop decision making in dynamic traffic environments. Latent world models offer an effective framework fo

local-aiarxiv-cs-lg

Operationalising Multi-Dimensional Evaluation for Conversational Agents: A Scalable, Governed Pipeline with Selective Re-evaluation and Model Benchmarking

arXiv:2607.12085v1 Announce Type: new Abstract: Evaluating retail conversational agents requires methods beyond lexical-overlap metrics to assess intent alignment, factuality, helpfulness, clarity, to

safetyarxiv-cs-ai

RAFP: Identifying LLM Lineages via Rare-Region Fingerprints

model-releasesarxiv-cs-lg

arXiv:2505.12682v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly released under restricted licenses, creating a growing need for robust model ownership verification. E

Structure-Semantic Co-optimized Latent Diffusion Model for Fast Visual Anagram Synthesis

arXiv:2606.16241v3 Announce Type: replace Abstract: Visual anagram is an intriguing form of art creation wherein a single image presents different conceptual interpretations under transformations such

safetyarxiv-cs-cv

ViCo3D: Empowering LiDAR-based Collaborative 3D Object Detection with Vision Foundation Models

arXiv:2607.12959v1 Announce Type: new Abstract: LiDAR-based collaborative 3D perception in Vehicle-to-Everything (V2X) systems typically relies on fusing bird's-eye-view (BEV) features across agents.

agentsarxiv-cs-cv

Agentic AI and Retrieval-Augmented Models in Straight-Through Underwriting

arXiv:2607.07858v1 Announce Type: new Abstract: Artificial intelligence (AI) is beginning to reshape actuarial practice, particularly in domains that require reasoning over unstructured documents, het

agentsarxiv-cs-ai

AI-integrated models for assessing agricultural resilience

arXiv:2607.07759v1 Announce Type: new Abstract: Agricultural supply chains are vulnerable to disruptions through linked biophysical and economic systems. We develop an AI-powered tool that integrates

Another big langchain week

model-releasesharrison-chase--x

Another big langchain week 🚀langchain launches this week: all about open source models and memory! First: open source models. We partnered with @NVIDIAAI to launch a NemoClaw DeepAgents blueprint. Thi

Bayesian Deep Learning for Discrete Choice

model-releasesarxiv-cs-lg

arXiv:2505.18077v3 Announce Type: replace-cross Abstract: Discrete choice models (DCMs) are used to analyze individual decision-making in contexts such as transportation choices, political elections,

Frontier and Center: Who evaluates the evaluations?

model-releasesgoogle-cloud-ai

Editor’s note: Some of the most interesting questions in AI are being asked by information theoreticians, around how to provide context to an emerging class of AI agents. A few weeks ago, we waded int

MuScriptor: An Open Model for Multi-Instrument Music Transcription

arXiv:2607.08168v1 Announce Type: cross Abstract: Existing methods for automatic music transcription are often limited to single-instrument recordings or fail on complex, real music mixes. Although pr

applicationsarxiv-cs-lg

Overthinking: Amplifying Reasoning Weights to Extract Learned Secrets

arXiv:2607.08173v1 Announce Type: new Abstract: Black box auditing of language models is an essential pre-deployment tool, but it may miss subtle forms of misalignment and hidden information. To bette

Predicting Viticulture Potential through an Ensemble of U-Net and a Geospatial Foundation Model

arXiv:2607.08449v1 Announce Type: new Abstract: Determining agricultural potential is fundamental to sustainable land management and agricultural planning. Remote sensing data is increasingly valuable

researcharxiv-cs-cv

Robustness Quantification for Discriminative Models: a New Robustness Metric and its Application to Dynamic Classifier Selection

arXiv:2603.23318v2 Announce Type: replace Abstract: Among the different possible strategies for evaluating the reliability of individual predictions of classifiers, robustness quantification stands ou

researcharxiv-cs-lg

Time-to-Collision Based Dynamic Obstacle Avoidance Using Pretrained Vision Models for Robots in Unstructured Environments

arXiv:2607.07885v1 Announce Type: cross Abstract: Dynamic obstacle avoidance in unstructured outdoor environments remains a critical challenge for autonomous mobile robots, particularly when large-sca

agentsarxiv-cs-ai

Ad Headline Generation using Self-Critical Masked Language Model

arXiv:2607.06818v1 Announce Type: cross Abstract: For any E-commerce website it is a nontrivial problem to build enduring advertisements that attract shoppers. It is hard to pass the creative quality

safetyarxiv-cs-ai

L-GTA: Latent Generative Modeling for Time Series Augmentation

arXiv:2507.23615v2 Announce Type: replace-cross Abstract: Data augmentation is becoming increasingly important across various areas of time series analysis, including forecasting, classification, and

applicationsarxiv-cs-ai

Mindbeam sets generative AI models to task on drug design, hunting for better pain meds

Enterprise artificial intelligence infrastructure startup Mindbeam AI Inc. today published research showing how generative AI can aid in the discovery of safer pain-relief drugs. The company used acet

applicationssiliconangle

Parametric and Generative Forecasts of EPEX Dayhar45 Ahead Energy Market Curves

model-releasesarxiv-cs-lg

arXiv:2601.20226v2 Announce Type: replace Abstract: We propose two methodologies for modelling aggregated supply and demand curves in the EPEX SPOT Dayhar45 Ahead market, emphasizing generative models

Safe Reinforcement Learning using Ideas from Model Predictive Control

arXiv:2607.07252v1 Announce Type: new Abstract: Reinforcement learning (RL) enables the synthesis of control policies directly from data, making it highly appealing for complex cyber-physical systems

safetyarxiv-cs-lg

Self-Supervised Pretraining Improves Cross-Site and Cross-Scale Robustness of Point Cloud Leaf-Wood Segmentation

arXiv:2607.06948v1 Announce Type: cross Abstract: The accuracy of existing leaf-wood segmentation methods for tree point clouds varies across forest types and sites. Self-supervised learning (SSL) on