Search: “models”

Chain-of-Procedure: Hierarchical Visual-Language Reasoning for Procedural QA

model-releasesarxiv-cs-cl

arXiv:2605.14928v1 Announce Type: new Abstract: Recent advances in vision-language models (VLMs) have achieved impressive results on standard image-text tasks, yet their potential for visual procedure

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Model Releases

Collider-Bench: Benchmarking AI Agents with Particle Physics Analysis Reproduction

DGX agent

arXiv:2605.13950v1 Announce Type: cross Abstract: Autonomous language-model agents are increasingly evaluated on long-horizon tool-use tasks, but existing benchmarks rarely capture the complexity and

model-releasesarxiv-cs-ai

15 May 2026

CRANE: Constrained Reasoning Injection for Code Agents via Nullspace Editing

arXiv:2605.14084v1 Announce Type: cross Abstract: Code agents must both reason over long-horizon repository state and obey strict tool-use protocols. In paired Instruct/Thinking checkpoints, these cap

CrystalReasoner: Reasoning and RL for Property-Conditioned Crystal Structure Generation

arXiv:2605.14344v1 Announce Type: new Abstract: Generative modeling has emerged as a promising approach for crystal structure discovery. However, existing LLM-based generative models struggle with low

safetyarxiv-cs-ai

Discovering Physical Directions in Weight Space: Composing Neural PDE Experts

arXiv:2605.14546v1 Announce Type: new Abstract: Recent advances in neural operators have made partial differential equation (PDE) surrogate modeling increasingly scalable and transferable through larg

DVMap: Fine-Grained Pluralistic Value Alignment via High-Consensus Demographic-Value Mapping

arXiv:2605.14420v1 Announce Type: new Abstract: Current Large Language Models (LLMs) typically rely on coarse-grained national labels for pluralistic value alignment. However, such macro-level supervi

Editor's Choice: Evaluating Abstract Intent in Image Editing through Atomic Entity Analysis

arXiv:2605.14842v1 Announce Type: new Abstract: Humans naturally communicate through abstract concepts like 'mood'. However, current image editing benchmarks focus primarily on explicit, literal comma

Elastic Spiking Transformers for Efficient Gesture Understanding

arXiv:2605.13869v1 Announce Type: cross Abstract: Spiking Neural Networks (SNNs), particularly Spiking Transformers, offer energy-efficient processing of event-based sensor data for healthcare applica

Good to Go: The LOOP Skill Engine That Hits 99% Success and Slashes Token Usage by 99% via One-Shot Recording and Deterministic Replay

arXiv:2605.14237v1 Announce Type: new Abstract: Deploying AI agents for repetitive periodic tasks exposes a critical tension: Large Language Models (LLMs) offer unmatched flexibility in tool orchestra

GraphBit: A Graph-based Agentic Framework for Non-Linear Agent Orchestration

arXiv:2605.13848v1 Announce Type: new Abstract: Agentic LLM frameworks that rely on prompted orchestration, where the model itself determines workflow transitions, often suffer from hallucinated routi

Hierarchical Image Tokenization for Multi-Scale Image Super Resolution

arXiv:2605.14891v1 Announce Type: new Abstract: We introduce a multi-scale Image Super Resolution (ISR) method building on recent advances in Visual Auto-Regressive (VAR) modeling. VAR models break im

safetyarxiv-cs-cv

JointAVBench: A Benchmark for Joint Audio-Visual Reasoning Evaluation

arXiv:2512.12772v2 Announce Type: replace-cross Abstract: Understanding videos inherently requires reasoning over both visual and auditory information. To properly evaluate Omni-Large Language Models

Kolmogorov-Arnold Chemical Reaction Neural Networks for learning pressure-dependent kinetic rate laws

arXiv:2511.07686v2 Announce Type: replace-cross Abstract: Chemical Reaction Neural Networks (CRNNs) have emerged as an interpretable machine learning framework for discovering reaction kinetics direct

Krause Synchronization Transformers

arXiv:2602.11534v3 Announce Type: replace-cross Abstract: Self-attention in Transformers relies on globally normalized softmax weights, causing all tokens to compete for influence at every layer. When

Tutorials

Memory-SAM: Human-Prompt-Free Tongue Segmentation via Retrieval-to-Prompt

arXiv:2510.15849v2 Announce Type: replace Abstract: Accurate tongue segmentation is crucial for reliable TCM analysis. Supervised models require large annotated datasets, while SAM-family models remai

tutorialsarxiv-cs-cv

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

Physics-Grounded Adversarial Stain Augmentation with Calibrated Coverage Guarantees

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

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

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

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