Search: “framework”

arXiv:2606.09112v1 Announce Type: cross Abstract: The rapid evolution of artificial intelligence has led to substantial advances in deep neural networks. Nonetheless, conventional GPU-based training r

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I-Segmenter: Integer-Only Vision Transformer for Efficient Semantic Segmentation

DGX agent

arXiv:2509.10334v2 Announce Type: replace-cross Abstract: Vision Transformers (ViTs) have recently achieved strong results in semantic segmentation, yet their deployment on resource-constrained device

applicationsarxiv-cs-ai

9 Jun 2026

'I understand your perspective': LLM Persuasion and Sycophancy through the Lens of Communicative Action Theory

arXiv:2606.08076v1 Announce Type: cross Abstract: Large Language Models (LLMs) can generate high-quality arguments, yet their ability to engage in nuanced and persuasive communicative actions remains

Identifiability and Estimation for Unlabeled Finite Mixtures under Marginal Independence

arXiv:2606.07914v1 Announce Type: cross Abstract: We study component recovery and mixing-matrix estimation from unlabeled finite mixtures whose observable distributions share the same latent component

IGenBench: Benchmarking the Reliability of Text-to-Infographic Generation

model-releasesarxiv-cs-cv

arXiv:2601.04498v2 Announce Type: replace-cross Abstract: Infographics are composite visual artifacts that combine data visualizations with textual and illustrative elements to communicate information

iMaC: Translating Actions into Motion and Contact Images for Embodied World Models

arXiv:2606.09813v1 Announce Type: cross Abstract: Embodied world models have emerged as a pivotal paradigm for visual robotic decision-making and interactive environment simulation. However, conventio

applicationsarxiv-cs-cv

Agents

In-Context Reinforcement Learning via Communicative World Models

arXiv:2508.06659v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) agents often struggle to generalize to new tasks and contexts without updating their parameters, mainly because th

agentsarxiv-cs-ai

Industrial policy for the Intelligence Age

This OpenAI publication likely discusses how governments and policymakers should approach industrial policy in an era dominated by artificial intelligence and computational intelligence capabilities.

safetyopenai

Inference-Time Conformal Reasoning with Valid Factuality Control for Large Language Models

arXiv:2606.08831v1 Announce Type: new Abstract: Large language models (LLMs) increasingly perform multi-step reasoning, where intermediate claims form implicit directed acyclic graphs whose node corre

Inferring hidden forcing in a biological oscillator using Kolmogorov-Arnold networks

arXiv:2606.08479v1 Announce Type: new Abstract: Inferring the forces that drive a dynamical system from partial observations is a fundamental challenge across physics, particularly when distinct under

Information-Theoretic Requirements for Gradient-Based Task Affinity Estimation in Multi-Task Learning

arXiv:2604.07848v2 Announce Type: replace Abstract: Multi-task learning shows strikingly inconsistent results -- sometimes joint training helps substantially, sometimes it actively harms performance -

safetyarxiv-cs-lg

Initial impressions of Claude Fable 5

model-releasessimon-willison

I didn't have early access to today's Claude Fable 5 release, but I've spent the past ~5.5 hours putting it through its paces. My initial impressions are that this is something of a beast. It's slow,

Insertion Based Sequence Generation with Learnable Order Dynamics

arXiv:2602.18695v2 Announce Type: replace Abstract: Existing insertion-based masked diffusion models that generate sequences by interleaving token insertion with unmasking use fixed schedules that are

IntentNav: Learning Spatial-Visual Object Navigation from Human Demonstrations

arXiv:2606.08029v1 Announce Type: new Abstract: Object navigation requires a robot to search for an unobserved target in an unknown environment by deciding where to explore next under partial observab

safetyarxiv-cs-ro

Inverse design of bespoke interatomic potentials via active learning by information-matching

model-releasesarxiv-cs-lg

arXiv:2606.08148v1 Announce Type: cross Abstract: Interatomic potentials (IPs) enable large-scale atomistic simulations beyond the reach of first-principles methods, but their predictive reliability d

Joint Structural Pruning and Mixed-Precision Quantization for LLM Compression

arXiv:2606.07819v1 Announce Type: new Abstract: Recently, the efficiency of Large Language Models (LLMs) deployment has become a critical concern in practical applications. While post-training quantiz

KITE: A Tri-Modal Transformer Integrating Text, Images, and Knowledge Graphs for Fake News Detection

model-releasesarxiv-cs-cv

arXiv:2606.07651v1 Announce Type: cross Abstract: Traditional fake news detection methods are falling behind as multimodal misinformation grows more advanced, seamlessly blending deceptive text, manip

KPGrasp: Scalable Keypoint Flow Matching for Dexterous Grasp Generation

model-releasesarxiv-cs-ro

arXiv:2606.09314v1 Announce Type: new Abstract: Generating high-quality dexterous grasps remains challenging for learning-based methods, which often depend on carefully tuned contact losses or costly

Language as a Sensor: Calibrated Spatial Belief Estimation in 3D Scenes from Natural Language

model-releasesarxiv-cs-ro

arXiv:2606.08666v1 Announce Type: new Abstract: Robots deployed in human-centric environments routinely receive natural-language descriptions of spatial information ('I left my backpack on the table')

Language-based Trial and Error Falls Behind in the Era of Experience

model-releasesarxiv-cs-ai

arXiv:2601.21754v3 Announce Type: replace Abstract: While Large Language Models (LLMs) excel in language-based agentic tasks, their applicability to unseen, nonlinguistic environments (e.g., symbolic

Larch: Learned Query Optimization for Semantic Predicates

arXiv:2606.07923v1 Announce Type: cross Abstract: With the advent of Large Language Models (LLMs), many database systems introduced semantic operators that enabled analytical queries over unstructured

applicationsarxiv-cs-ai

Large Language Models Should Learn Personalized Rather Than Aggregated Human Preferences

arXiv:2606.07629v1 Announce Type: cross Abstract: Current approaches to aligning large language models (LLMs) aggregate diverse human preferences into a single reward signal, effectively optimizing fo

Late-Layer Fusion is Enough: Dual-Path Vision Token Routing for Multimodal Large Language Models under Visual Saturation

arXiv:2606.09131v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) commonly inherit the deep, symmetric Transformer backbone designed for unimodal text modeling, and apply the sa

Latent Diffusion Policy: Shaping Latent Spaces for Diffusion-Based Robotic Manipulation

arXiv:2606.08657v1 Announce Type: cross Abstract: Diffusion-based visuomotor policies operating directly in raw action spaces conflate scene comprehension with trajectory generation within a single de

Latent Spatial Memory for Video World Models

arXiv:2606.09828v1 Announce Type: new Abstract: Video world models that maintain 3D spatial consistency across generated frames typically rely on explicit point cloud memory constructed in RGB space.

researcharxiv-cs-cv

Latent Structural Categorical Matrix Completion with Application to Quasispecies Analysis

arXiv:2606.08188v1 Announce Type: cross Abstract: Matrix completion has been extensively studied for real-valued data, but existing methods are often limited in handling categorical variables. We prop

applicationsarxiv-cs-lg

Learnable Token Sparsification for Efficient Gigapixel Whole Slide Image Reasoning

arXiv:2606.08641v1 Announce Type: new Abstract: The processing of gigapixel whole slide images within vision language models faces a major difficulty due to an excessive number of visual tokens. Exist

tutorialsarxiv-cs-cv

Learning to Attack and Defend: Adaptive Red Teaming of Language Models via GRPO

arXiv:2606.09701v1 Announce Type: cross Abstract: AI red teaming must continually adapt to evolving attackers and defenders. Reinforcement learning offers a promising approach to discovering novel att

Learning to Optimize by Differentiable Programming

arXiv:2601.16510v3 Announce Type: replace-cross Abstract: Solving massive-scale optimization problems requires scalable first-order methods with low per-iteration cost. This tutorial highlights a shif

tutorialsarxiv-cs-lg

LiteVSR: Lightweight Adaptation of Frozen Diffusion Transformers for Video Super-Resolution

arXiv:2606.09250v1 Announce Type: new Abstract: Adapting large-scale pre-trained video generators for Video Super-Resolution (VSR) in novel domains remains computationally prohibitive. Methods that re

safetyarxiv-cs-cv

Locally Adaptive Conformal Inference for Operator Models

arXiv:2507.20975v5 Announce Type: replace-cross Abstract: Operator models are regression algorithms between Banach spaces of functions. They have become an increasingly critical tool for spatiotempora

local-aiarxiv-cs-lg

Loss-Guided Adaptive Scale Refinement for Molecular Force Prediction

arXiv:2606.09480v1 Announce Type: new Abstract: Molecular systems involve interactions across multiple spatial scales, from local coordination and short-range perturbations to long-range electrostatic

LUNA-AD: Lightweight Uncertainty-Aware Language Model with Lifelong Learning for Autonomous Driving

arXiv:2606.08470v1 Announce Type: new Abstract: While large language models (LLMs) offer promising reasoning capabilities, their integration into safety-critical driving systems is hindered by limited

safetyarxiv-cs-ro

MAGIS: Evidence-Based Multi-Agent Reasoning for Interpretable Strabismus Clinical Decision-Making

model-releasesarxiv-cs-cv

arXiv:2606.09249v1 Announce Type: new Abstract: Strabismus is a common ocular disorder that requires fine-grained subtype diagnosis for individualized treatment planning. However, existing deep learni

MatMind: A Structure-Activity Knowledge-Driven Generative Foundation Model for Materials Science

arXiv:2606.07712v1 Announce Type: cross Abstract: Progress in AI-driven crystal materials science has so far been carried by narrow architectures purpose-built for individual tasks -- graph neural net

Agents

MAVIS: Multi-Agent Video Retrieval via Structured Video Understanding

arXiv:2606.09641v1 Announce Type: new Abstract: The dominant paradigm in video retrieval relies on embedding-based full-corpus scanning, which suffers from inherent computational inefficiency and the

agentsarxiv-cs-cv

MB-Loc: Multi-planar Bird's-eye-view Localization in outdoor LiDAR scenes

arXiv:2606.08744v1 Announce Type: new Abstract: Global LiDAR localization is a fundamental task for autonomous navigation systems. Recent methods perform Scene Coordinate Regression (SCR) and achieve

local-aiarxiv-cs-cv

MC-CPO: Mastery-Conditioned Constrained Policy Optimization for Pedagogically Safe Intelligent Tutoring Systems

arXiv:2604.04251v2 Announce Type: replace Abstract: Intelligent tutoring systems increasingly rely on reinforcement learning to personalise instruction, yet optimising for observable engagement signal

Mechanistic Data Attribution: Tracing the Training Origins of Interpretable LLM Units

arXiv:2601.21996v2 Announce Type: replace-cross Abstract: While Mechanistic Interpretability has identified interpretable circuits in LLMs, their causal origins in training data remain elusive. We int

Hardware

Meeting SLOs, Slashing Hours: Automated Enterprise LLM Optimization with OptiKIT

arXiv:2601.20408v2 Announce Type: replace-cross Abstract: Enterprise LLM deployment faces a critical scalability challenge: organizations must optimize models systematically to scale AI initiatives wi

hardwarearxiv-cs-ai

MemoryVLA++: Temporal Modeling via Memory and Imagination in Vision-Language-Action Models

arXiv:2606.09827v1 Announce Type: cross Abstract: Temporal modeling is essential for robotic manipulation, as effective control requires both memory of past interactions and imagination of future stat

researcharxiv-cs-cv

MemoVAD: Resource-Efficient Video Anomaly Detection via Dynamic Semantic Memory in Edge Computing Scenarios

arXiv:2606.07669v1 Announce Type: cross Abstract: Deploying Video Anomaly Detection (VAD) in real-world surveillance faces a fundamental tension between the demand for high-level semantics to ensure e

local-aiarxiv-cs-ai

Agents

MemToolAgent overview with a simple restaurant booking scenario where the agent retrieves similar memories, receives feedback on an invalid time format, and generates a reflection to update its memory

arXiv:2606.07909v1 Announce Type: new Abstract: Modern large language model (LLM) agents can use external tools to help users solve complex tasks. However, for problems that require learning from long

agentsarxiv-cs-ai

MEnvAgent: Scalable Polyglot Environment Construction for Verifiable Software Engineering

model-releasesarxiv-cs-ai

arXiv:2601.22859v3 Announce Type: replace-cross Abstract: The evolution of Large Language Model (LLM) agents for software engineering (SWE) is constrained by the scarcity of verifiable datasets, a bot

Minimal Solvers for Full-DoF Motion Estimation from Asynchronous Differential SfM

arXiv:2606.09218v1 Announce Type: new Abstract: As a bio-inspired intelligent sensor, event cameras have introduced a new paradigm in the intelligent perception of spatiotemporal information and visua

applicationsarxiv-cs-cv

Mitigating the Contractivity Trap in Diffusion ODEs via Stein Stabilization

arXiv:2606.07835v1 Announce Type: new Abstract: A fundamental tension exists in the large-step inference of diffusion models via their deterministic probability flow ordinary differential equation (PF

local-aiarxiv-cs-lg

MixReasoning: Switching Modes to Think

arXiv:2510.06052v2 Announce Type: replace Abstract: Reasoning models enhance performance by tackling problems in a step-by-step manner, decomposing them into sub-problems and exploring long chains of

tutorialsarxiv-cs-ai

Mobility-Embedded POIs: Learning What A Place Is and How It Is Used from Human Movement

arXiv:2601.21149v3 Announce Type: replace-cross Abstract: Recent progress in geospatial foundation models highlights the importance of learning general-purpose representations for real-world locations

tutorialsarxiv-cs-ai