Search: “models”

Peng's Q(lambda) for Conservative Value Estimation in Offline Reinforcement Learning

arXiv:2605.14779v1 Announce Type: new Abstract: We propose a model-free offline multi-step reinforcement learning (RL) algorithm, Conservative Peng's Q(lambda) (CPQL). Our algorithm adapts the Peng's

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Physics-Grounded Adversarial Stain Augmentation with Calibrated Coverage Guarantees

DGX agent

arXiv:2605.13889v1 Announce Type: cross Abstract: Stain variation across hospitals degrades histopathology models at deployment. Existing augmentation methods perturb color spaces with arbitrary hyper

model-releasesarxiv-cs-cv

15 May 2026

pi-Bench: Evaluating Proactive Personal Assistant Agents in Long-Horizon Workflows

arXiv:2605.14678v1 Announce Type: new Abstract: The rise of personal assistant agents, e.g., OpenClaw, highlights the growing potential of large language models to support users across everyday life a

PreFT: Prefill-only finetuning for efficient inference

arXiv:2605.14217v1 Announce Type: cross Abstract: Large language models can now be personalised efficiently at scale using parameter efficient finetuning methods (PEFTs), but serving user-specific PEF

RefDecoder: Enhancing Visual Generation with Conditional Video Decoding

arXiv:2605.15196v1 Announce Type: new Abstract: Video generation powers a vast array of downstream applications. However, while the de facto standard, i.e., latent diffusion models, typically employ h

Reinforcement Learning for Tool-Calling Agents in Fast Healthcare Interoperability Resources (FHIR)

arXiv:2605.14126v1 Announce Type: cross Abstract: Fast Healthcare Interoperability Resources (FHIR) is the dominant standard for interoperable exchange of healthcare data. In FHIR, electronic health r

Safe Bayesian Optimization for Complex Control Systems via Additive Gaussian Processes

arXiv:2408.16307v3 Announce Type: replace-cross Abstract: Automatic controller tuning is attractive for robotics and mechatronic systems whose dynamics are difficult to model accurately, but direct bl

Sat3DGen: Comprehensive Street-Level 3D Scene Generation from Single Satellite Image

arXiv:2605.14984v1 Announce Type: cross Abstract: Generating a street-level 3D scene from a single satellite image is a crucial yet challenging task. Current methods present a stark trade-off: geometr

SD-ReID: View-aware Stable Diffusion for Aerial-Ground Person Re-Identification

arXiv:2504.09549v3 Announce Type: replace Abstract: Aerial-Ground Person Re-IDentification (AG-ReID) aims to retrieve specific persons across cameras with different viewpoints. Previous works focus on

researcharxiv-cs-cv

Safety

Selective Safety Steering via Value-Filtered Decoding

arXiv:2605.14746v1 Announce Type: new Abstract: While large language models (LLMs) are trained to align with human values, their generations may still violate safety constraints. A growing line of wor

safetyarxiv-cs-lg

Agents

Silent Collapse in Recursive Learning Systems

arXiv:2605.14588v1 Announce Type: new Abstract: Recursive learning -- where models are trained on data generated by previous versions of themselves -- is increasingly common in large language models,

agentsarxiv-cs-lg

Stochastic Attention via Langevin Dynamics on the Modern Hopfield Energy

arXiv:2603.06875v3 Announce Type: replace Abstract: Attention heads retrieve: given a query, they return a weighted average of stored values. We showed that this computation is one step of gradient de

The Rate-Distortion-Polysemanticity Tradeoff in SAEs

arXiv:2605.14694v1 Announce Type: new Abstract: Sparse Autoencoders (SAEs) that can accurately reconstruct their input (minimizing distortion) by making efficient use of few features (minimizing the r

Towards the Next Frontier of LLMs, Training on Private Data: A Cross-Domain Benchmark for Federated Fine-Tuning

arXiv:2605.13936v1 Announce Type: cross Abstract: The recent success of large language models (LLMs) has been largely driven by vast public datasets. However, the next frontier for LLM development lie

VER: Vision Expert Transformer for Robot Learning via Foundation Distillation and Dynamic Routing

arXiv:2510.05213v2 Announce Type: replace-cross Abstract: Pretrained vision foundation models (VFMs) advance robotic learning via rich visual representations, yet individual VFMs typically excel only

Safety

VGGT-Omega

arXiv:2605.15195v1 Announce Type: new Abstract: Recent feed-forward reconstruction models, such as VGGT, have proven competitive with traditional optimization-based reconstructors while also providing

safetyarxiv-cs-cv

VLRS-Bench: A Vision-Language Reasoning Benchmark for Remote Sensing

arXiv:2602.07045v2 Announce Type: replace-cross Abstract: Recent advancements in Multimodal Large Language Models (MLLMs) have enabled complex reasoning. However, existing remote sensing (RS) benchmar

VMU-Diff: A Coarse-to-fine Multi-source Data Fusion Framework for Precipitation Nowcasting

arXiv:2605.14597v1 Announce Type: new Abstract: Precipitation nowcasting is a vital spatio-temporal prediction task for meteorological applications but faces challenges due to the chaotic property of

researcharxiv-cs-cv

Local Ai

Watch your neighbors: Training statistically accurate chaotic systems with local phase space information

arXiv:2605.14405v1 Announce Type: new Abstract: Chaotic systems pose fundamental challenges for data-driven dynamics discovery, as small modeling errors lead to exponentially growing trajectory discre

local-aiarxiv-cs-lg

Web Agents Should Adopt the Plan-Then-Execute Paradigm

arXiv:2605.14290v1 Announce Type: cross Abstract: ReAct has become the default architecture across LLM agents, and many existing web agents follow this paradigm. We argue that it is the wrong default

Why Retrieval-Augmented Generation Fails: A Graph Perspective

arXiv:2605.14192v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) has become a powerful and widely used approach for improving large language models by grounding generation in ret

researcharxiv-cs-ai

XDomainBench: Diagnosing Reasoning Collapse in High-Dimensional Scientific Knowledge Composition

arXiv:2605.14754v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed for knowledge synthesis, yet their capacity for compositional generalization in scientific knowle

Local Ai

AIvaluateXR: An Evaluation Framework for on-Device AI in XR with Benchmarking Results

arXiv:2502.15761v3 Announce Type: replace-cross Abstract: The deployment of large language models (LLMs) on extended reality (XR) devices has great potential to advance the field of human-AI interacti

local-aiarxiv-cs-ai

Bayesian In Vivo Tracking of Synapses using Joint Poisson Deconvolution and Diffeomorphic Registration

arXiv:2605.13455v1 Announce Type: new Abstract: Synapses are densely packed submicron structures that dynamically reorganize during learning and memory formation. Longitudinal extit{in vivo} imaging o

Cross Modality Image Translation In Medical Imaging Using Generative Frameworks

arXiv:2605.13686v1 Announce Type: cross Abstract: Medical image-to-image (I2I) translation enables virtual scanning, i.e. the synthesis of a target imaging modality from a source one without additiona

researcharxiv-cs-ai

Tutorials

DiscoverLLM: From Executing Intents to Discovering Them

arXiv:2602.03429v2 Announce Type: replace Abstract: To handle ambiguous and open-ended requests, Large Language Models (LLMs) are increasingly trained to interact with users to surface intents they ha

tutorialsarxiv-cs-ai

Effective Context in Transformers: An Analysis of Fragmentation and Tokenization

arXiv:2605.13485v1 Announce Type: new Abstract: Transformers predict over a representation of a sequence. The same data can be written as bytes, characters, or subword tokens, and these representation

Hardware

EMO: Frustratingly Easy Progressive Training of Extendable MoE

arXiv:2605.13247v1 Announce Type: new Abstract: Sparse Mixture-of-Experts (MoE) models offer a powerful way to scale model size without increasing compute, as per-token FLOPs depend only on k active e

hardwarearxiv-cs-lg

GHGbench: A Unified Multi-Entity, Multi-Task Benchmark for Carbon Emission Prediction

arXiv:2605.13743v1 Announce Type: new Abstract: Open datasets and benchmarks for entity-level carbon-emission prediction remain fragmented across access, scale, granularity, and evaluation. We introdu

Grid-Orch: An LLM-Powered Orchestrator for Distribution Grid Simulation and Analytics

arXiv:2605.12728v1 Announce Type: cross Abstract: The power distribution engineering workforce faces a projected shortage of up to 1.5 million engineers by 2030, creating urgent demand for more access

HADAR-Based Thermal Infrared Hyperspectral Image Restoration

arXiv:2605.13664v1 Announce Type: new Abstract: Thermal-infrared (TIR) hyperspectral imagery (HSI) provides critical scene information for various applications. However, its practical utility is sever

Just Ask for a Table: A Thirty-Token User Prompt Defeats Sponsored Recommendations in Twelve LLMs

arXiv:2605.12772v1 Announce Type: new Abstract: Wu et al. (2026) showed that most frontier large language models (LLMs) recommend a sponsored, roughly twice-as-expensive flight when their system promp

researcharxiv-cs-cv

Kiwi-Edit: Versatile Video Editing via Instruction and Reference Guidance

arXiv:2603.02175v4 Announce Type: replace-cross Abstract: Instruction-based video editing has witnessed rapid progress, yet current methods often struggle with precise visual control, as natural langu

Local Ai

Layer-wise Representation Dynamics: An Empirical Investigation Across Embedders and Base LLMs

arXiv:2605.12714v1 Announce Type: new Abstract: Hidden states change substantially across the layers of modern language models, but most layer-wise analyses focus on one aspect of that change. We prop

local-aiarxiv-cs-lg

Low-Rank Adapters Initialization via Gradient Surgery for Continual Learning

arXiv:2605.12752v1 Announce Type: new Abstract: LoRA is widely adopted for continual fine-tuning of Large Language Models due to its parameter efficiency, modularity across tasks, and compatibility wi

OmniLiDAR: A Unified Diffusion Framework for Multi-Domain 3D LiDAR Generation

arXiv:2605.13815v1 Announce Type: new Abstract: LiDAR scene generation is increasingly important for scalable simulation and synthetic data creation, especially under diverse sensing conditions that a

Orthrus: Memory-Efficient Parallel Token Generation via Dual-View Diffusion

arXiv:2605.12825v1 Announce Type: cross Abstract: We introduce Orthrus, a simple and efficient dual-architecture framework that unifies the exact generation fidelity of autoregressive Large Language M

OSDN: Improving Delta Rule with Provable Online Preconditioning in Linear Attention

arXiv:2605.13473v1 Announce Type: new Abstract: Linear attention and state-space models offer constant-memory alternatives to softmax attention, but often struggle with in-context associative recall.

Agents

Parallel-in-Time Training of Recurrent Neural Networks for Dynamical Systems Reconstruction

arXiv:2605.12683v1 Announce Type: cross Abstract: Reconstructing nonlinear dynamical systems (DS) from data (DSR) is a fundamental challenge in science and engineering, but it inherently relies on seq

agentsarxiv-cs-ai

PERCEIVE: A Benchmark for Personalized Emotion and Communication Behavior Understanding on Social Media

arXiv:2605.12525v1 Announce Type: cross Abstract: Current emotion analysis in social media is predominantly author-centric, failing to capture the subjective nature of emotional responses across diver

PhysEditBench: A Protocol-Conditioned Benchmark for Dense Physical-Map Prediction with Image Editors

arXiv:2605.13493v1 Announce Type: new Abstract: Can general-purpose image editors predict physical maps from a single RGB image? General-purpose image editors differ from standard task-specific dense-

PreFIQs: Face Image Quality Is What Survives Pruning

arXiv:2605.13396v1 Announce Type: new Abstract: Face Image Quality Assessment (FIQA) evaluates the utility of a face image for automated face recognition (FR) systems. In this work, we propose PreFIQs

Qwen-Image-VAE-2.0 Technical Report

arXiv:2605.13565v1 Announce Type: new Abstract: We present Qwen-Image-VAE-2.0, a suite of high-compression Variational Autoencoders (VAEs) that achieve significant advances in both reconstruction fide

RS-Claw: Progressive Active Tool Exploration via Hierarchical Skill Trees for Remote Sensing Agents

arXiv:2605.13391v1 Announce Type: new Abstract: The rise of multi-modal large language models (MLLMs) is shifting remote sensing (RS) intelligence from 'see' to 'action', as OpenClaw-style frameworks

Scaling Laws for Mixture Pretraining Under Data Constraints

arXiv:2605.12715v1 Announce Type: new Abstract: As language models scale, the amount of data they require grows -- yet many target data sources, such as low-resource languages or specialized domains,

researcharxiv-cs-lg

SCU-Hand with Integrated Single-Sheet Valve: A Funnel-Shaped Robotic Hand for Milligram-Scale Powder Handling

model-releasesarxiv-cs-ro

arXiv:2512.07091v2 Announce Type: replace Abstract: Laboratory Automation (LA) has the potential to accelerate solid-state materials discovery by enabling continuous robotic operation without human in

Safety

Spectral Energy Centroid: a Metric for Improving Performance and Analyzing Spectral Bias in Implicit Neural Representations

arXiv:2605.12709v1 Announce Type: new Abstract: Implicit Neural Representations (INRs) model continuous signals using multilayer perceptrons (MLPs), enabling compact, differentiable, and high-fidelity

safetyarxiv-cs-lg

SpectralTrain: A Universal Framework for Hyperspectral Image Classification

arXiv:2511.16084v2 Announce Type: replace-cross Abstract: Hyperspectral image (HSI) classification typically involves large-scale data and computationally intensive training, which limits the practica