Search: “models”

CAFOSat: A Strongly Annotated Dataset for Infrastructure-Aware CAFO Mapping Using High-Resolution Imagery

arXiv:2606.00548v1 Announce Type: cross Abstract: Concentrated Animal Feeding Operations (CAFOs) play an important role in agricultural production but are also associated with environmental, public he

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Local Ai

Capability Self-Assessment: Teaching LLMs to Know Their Limits

DGX agent

arXiv:2606.00251v1 Announce Type: new Abstract: The ability to recognize one's own limitations and decide whether to solve a problem or delegate is fundamental for reliable intelligent systems. Yet we

local-aiarxiv-cs-ai

2 Jun 2026

Local Ai

Certificates without Electrons? Theory and Evidence on Impacts from AI-Driven Power Demand

arXiv:2606.00811v1 Announce Type: cross Abstract: Data centers now account for 4.4% of United States electricity demand, yet the grid-level effectiveness of the renewable energy certificates (RECs) an

local-aiarxiv-cs-ai

Safety

CLAW: A Vision-Language-Action Framework for Weight-Aware Robotic Grasping

arXiv:2509.14143v2 Announce Type: replace Abstract: Vision-language-action (VLA) models have recently emerged as a promising paradigm for robotic control, enabling end-to-end policies that ground natu

safetyarxiv-cs-ro

Co-training with Ego-centric Video and Demonstration for Robot Navigation Task

arXiv:2606.01951v1 Announce Type: new Abstract: Vision-language-action (VLA) models are promising for diverse robotic tasks, but their performance heavily depends on large-scale high-quality training

researcharxiv-cs-ro

Concept Heterogeneity-aware Representation Steering

arXiv:2603.02237v2 Announce Type: replace-cross Abstract: Representation steering offers a lightweight mechanism for controlling the behavior of large language models (LLMs) by intervening on internal

CRAB-Bench: Evaluating LLM Agents under Complex Task Dependencies and Human-aligned User Simulation

arXiv:2606.01815v1 Announce Type: new Abstract: Evaluating LLM agents in realistic service scenarios requires complex task dependencies, imperfect user behavior, and an evaluation that accommodates mu

Hardware

CRAFT: Fine-Grained Cost-Aware Expert Replication For Efficient Mixture-of-Experts Serving

arXiv:2603.28768v2 Announce Type: replace-cross Abstract: Mixture-of-Experts (MoE) has recently emerged as the mainstream architecture for efficiently scaling large language models while maintaining n

hardwarearxiv-cs-lg

CURP: Codebook-based Continuous User Representation for Personalized Generation with LLMs

arXiv:2602.00742v2 Announce Type: replace Abstract: User modeling characterizes individuals through their preferences and behavioral patterns to enable personalized simulation and generation with Larg

researcharxiv-cs-cl

Design-MLLM: A Reinforcement Alignment Framework for Verifiable and Aesthetic Interior Design

model-releasesarxiv-cs-lg

arXiv:2603.13312v2 Announce Type: replace-cross Abstract: Interior design is a requirements-to-visual-plan generation process that must simultaneously satisfy verifiable spatial feasibility and compar

EEG-FuseFormer: A Transformer-Driven Feature Fusion Framework for Seizure Onset Prediction

arXiv:2606.02166v1 Announce Type: new Abstract: Epilepsy is one of the most common neurological disorders globally, characterized by recurring seizures and significantly impacting the quality of life.

researcharxiv-cs-lg

Ego-METAS: Egocentric online Multimodal Energy-efficient Temporal Action Segmentation benchmark

arXiv:2606.02246v1 Announce Type: new Abstract: To operate in the physical world, embodied agents must perceive their environment in an 'always-on' fashion, selectively accessing the most informative

Enhancing Blind Source Separation with Dissociative Principal Component Analysis

arXiv:2411.12321v2 Announce Type: replace Abstract: Principal component analysis (PCA) and its sparse variants (sPCA) are widely used as a precursor to independent component analysis (ICA) for blind s

Evaluating Reliability Asymmetries in Chinese Factual Search and AI Answers

arXiv:2602.22221v2 Announce Type: replace-cross Abstract: Search engines and AI-powered systems increasingly mediate access to factual information, yet their reliability remains difficult to evaluate

Safety

Fair Finetuning Mitigates Distribution Inference Attacks

arXiv:2606.01719v1 Announce Type: cross Abstract: Machine learning models trained on sensitive data can inadvertently leak population-level information about their training distributions -- a threat k

safetyarxiv-cs-ai

Local Ai

Fast Generalization after Interpolation via Critically Damped Momentum Optimization

arXiv:2606.01521v1 Announce Type: new Abstract: A central problem in machine learning is that models can achieve near-perfect training performance while generalizing substantially less well to unseen

local-aiarxiv-cs-lg

Faster Synchronous On-Policy RL via Straggler-Aware Group Sizing

arXiv:2606.02218v1 Announce Type: cross Abstract: Synchronous reinforcement learning methods such as Group Relative Policy Optimization (GRPO) provide stable and reproducible on-policy training, but t

FastSLM: Hierarchical Temporal Abstraction for Efficient Long-Form Speech Adaptation

arXiv:2601.06199v3 Announce Type: replace-cross Abstract: Scaling Multimodal Large Language Models (MLLMs) to long-form speech is bottlenecked by the explosive growth of input tokens. Unlike images or

Federated Learning via Variational Bayesian Inference: Personalization, Sparsity and Clustering

arXiv:2303.04345v2 Announce Type: replace Abstract: Federated learning (FL) is a promising framework that models distributed machine learning while protecting the privacy of clients. However, FL suffe

researcharxiv-cs-lg

Agents

FedS2R: One-Shot Federated Domain Generalization for Synthetic-to-Real Semantic Segmentation in Autonomous Driving

arXiv:2507.19881v2 Announce Type: replace-cross Abstract: Federated domain generalization has shown promising progress in image classification by enabling collaborative training across multiple client

agentsarxiv-cs-ai

FLAME: Physics-Guided Neural Operators for Onboard Satellite Methane Detection in Hyperspectral Imagery

arXiv:2606.01577v1 Announce Type: new Abstract: Methane is a major driver of near-term climate change, and rapidly identifying its emission sources is a critical climate intervention. Spaceborne hyper

Agents

Generative AI and Digital Ecosystem Resilience: A Proactive Lifecycle-Based Survey

arXiv:2606.00136v1 Announce Type: cross Abstract: The proliferation of adversarial synthetic content, accelerated by Generative AI (GenAI) is rendering traditional reactive detection methods ineffecti

agentsarxiv-cs-ai

Geometric Erasure by Contrastive Velocity Matching in Rectified Flows

arXiv:2606.00140v1 Announce Type: cross Abstract: While the rapid adoption of multimodal generative models offers immense potential, it has also increased the risks of harmful content synthesis, deepf

GREAT: Generalizable Backdoor Attacks in RLHF via Emotion-Aware Trigger Synthesis

model-releasesarxiv-cs-lg

arXiv:2510.09260v2 Announce Type: replace-cross Abstract: Recent work has shown that RLHF is highly susceptible to backdoor attacks. However, existing methods often rely on rare tokens or fixed trigge

Agents

How Generation Architecture Shapes Code Complexity in Multi-Agent LLM Systems: A Paired Study on HumanEval

arXiv:2606.00308v1 Announce Type: cross Abstract: Large-language-model code generation has shifted from single-shot prompting to multi-agent orchestrations - analyst, coder, tester, and debugger pipel

agentsarxiv-cs-ai

Hyperspherical Variational Autoencoders Using Efficient Spherical Cauchy Distribution

arXiv:2506.21278v3 Announce Type: replace-cross Abstract: We propose spherical Cauchy (spCauchy) latent variables for variational autoencoders on hyperspherical latent spaces. The spCauchy family has

hZACH-ViT: Curved Latent Geometry for Compact Vision Transformers in Low-Data Medical Imaging

arXiv:2606.00906v1 Announce Type: new Abstract: Compact Vision Transformers are attractive for medical imaging in low-data and resource-constrained settings, but most existing variants assume that Euc

IMAC-AgriVLN: Can Agricultural Vision-and-Language Navigation Agents be Aware of Instruction Mistakes?

model-releasesarxiv-cs-ro

arXiv:2606.02519v1 Announce Type: new Abstract: Agricultural robots are serving as powerful assistants across a wide range of agricultural tasks, nevertheless, still heavily relying on manual operatio

InstructSAM: Segment Any Instance with Any Instructions

arXiv:2605.26102v2 Announce Type: replace Abstract: In this paper, we introduce InstructSAM, a unified and streamlined framework designed for multi-instance segmentation under arbitrary instructions.

Safety

Joint Agent Memory and Exploration Learning via Novelty Signals

arXiv:2606.01528v1 Announce Type: new Abstract: In open-ended environments, exploration is fundamental for autonomous agents, yet current language model agents struggle with this. Effective exploratio

safetyarxiv-cs-ai

Latent Reward Steering: An Adaptive Inference-Time Framework that Implicitly Promotes Cognitive Behaviors in Reasoning LLMs

arXiv:2606.00726v1 Announce Type: new Abstract: Strong reasoning depends not only on model knowledge but also on how effectively cognitive behaviors are deployed during generation. Existing methods of

Local Ai

Learning Chaotic Dynamics through Second-Order Geometric Supervision

arXiv:2606.01596v1 Announce Type: cross Abstract: Learning chaotic dynamical systems from data requires more than short-term predictive accuracy: the learned model must preserve the attractor geometry

local-aiarxiv-cs-lg

Learning to Retrieve: Dual-Level Long-Term Memory for Text-to-SQL Agents

arXiv:2606.00547v1 Announce Type: new Abstract: Interactive text-to-SQL agents solve database tasks through multi-turn interactions involving schema exploration, query execution, feedback interpretati

Tutorials

Learning When to Translate for Multilingual Reasoning

arXiv:2606.02465v1 Announce Type: cross Abstract: Reasoning language models (RLMs) achieve strong performance on complex reasoning tasks, but still exhibit substantial multilingual reasoning gaps, lar

tutorialsarxiv-cs-ai

Applications

Linear Strategic Classification with Endogenous Improvements

arXiv:2606.01198v1 Announce Type: new Abstract: Strategic classification studies settings in which agents respond to a deployed classifier by modifying observable features at a cost. Classical models

applicationsarxiv-cs-lg

MASER: Modality-Adaptive Specialist Routing for Embodied 3D Spatial Intelligence

arXiv:2606.02463v1 Announce Type: cross Abstract: In 3D environments, Embodied Agents answer spatially relevant questions through reasoning from a mixture of modalities including natural language, RGB

MAVL: A Multilingual Audio-Video Lyrics Dataset for Animated Song Translation

arXiv:2505.18614v5 Announce Type: replace Abstract: Lyrics translation requires both accurate semantic transfer and preservation of musical rhythm, syllabic structure, and poetic style. In animated mu

Applications

MidSurfNet: Learnable Face Pairing and Interference Implicit Fields for Generalized Mid-surface Abstraction

arXiv:2606.01891v1 Announce Type: cross Abstract: Mid-surface abstraction is essential for finite element analysis of thin-walled CAD models. Existing face pairing-based methods rely on handcrafted ge

applicationsarxiv-cs-lg

Molecular Embedding-Based Algorithm Selection in Protein-Ligand Docking

model-releasesarxiv-cs-lg

arXiv:2512.02328v2 Announce Type: replace-cross Abstract: Selecting an effective docking algorithm is highly context-dependent, and no single method performs reliably across structural, chemical, and

MOSS-Audio Technical Report

arXiv:2606.01802v1 Announce Type: cross Abstract: MOSS-Audio is a unified audio-language model for speech, environmental sound, and music understanding, supporting audio captioning, time-aware questio

Motion-aware Event Suppression for Event Cameras

arXiv:2602.23204v3 Announce Type: replace Abstract: In this work, we introduce the first framework for Motion-aware Event Suppression, which learns to filter events triggered by IMOs and ego-motion in

Multi-Agent Computer Use

arXiv:2606.01533v1 Announce Type: cross Abstract: Computer use agents (CUAs) today are primarily deployed as single serial agents. This setup is suboptimal for complex long-horizon tasks that benefit

naPINN: Noise-Adaptive Physics-Informed Neural Networks for Recovering Physics from Corrupted Measurement

arXiv:2602.02547v2 Announce Type: replace-cross Abstract: Physics-Informed Neural Networks (PINNs) are effective methods for solving inverse problems and discovering governing equations from observati

Applications

Near-Optimal Pure Machine Unlearning for Smooth Strongly Convex Losses

arXiv:2606.01527v1 Announce Type: new Abstract: Machine unlearning is motivated by legal and user-facing requirements to remove the influence of individuals' data from trained models, such as the righ

applicationsarxiv-cs-lg

NILC: Discovering New Intents with LLM-assisted Clustering

arXiv:2511.05913v2 Announce Type: replace-cross Abstract: New intent discovery (NID) seeks to recognize both new and known intents from unlabeled user utterances, which finds prevalent use in practica

OpenWebRL: Demystifying Online Multi-turn Reinforcement Learning for Visual Web Agents

arXiv:2606.02031v1 Announce Type: cross Abstract: Building capable visual web agents requires long-horizon reasoning, precise grounding, and robust interaction with dynamic real-world websites. Despit

Optimizing accuracy and diversity: a multi-task approach to forecast combinations

arXiv:2310.20545v3 Announce Type: replace Abstract: We present a multi-task optimization approach based on a deep learning architecture for time series forecasting. We leverage large collections of ti

researcharxiv-cs-lg

PathAR: Structure-First Autoregressive Synthesis of Multimodal Pathology Images

arXiv:2606.01543v1 Announce Type: new Abstract: Data scarcity in multimodal pathology motivates unified generative models that synthesize modality-specific appearance while preserving anatomically coh

researcharxiv-cs-cv