Search: “framework”

From Raw Experience to Skill Consumption: A Systematic Study of Model-Generated Agent Skills

arXiv:2605.23899v1 Announce Type: new Abstract: Language agents increasingly improve by reusing skills -- structured procedural artifacts distilled from past experience. In particular, domain-level an

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Agents

From Residuals to Reasons: LLM-Guided Mechanism Inference from Tabular Data

DGX agent

arXiv:2605.22897v1 Announce Type: new Abstract: A persistent challenge in machine learning for scientific applications is jointly achieving prediction and understanding. Statistical models excel on st

agentsarxiv-cs-lg

25 May 2026

FuRA: Full-Rank Parameter-Efficient Fine-Tuning with Spectral Preconditioning

model-releasesarxiv-cs-lg

arXiv:2605.22869v1 Announce Type: new Abstract: Both full fine-tuning (Full FT) and parameter-efficient fine-tuning methods such as LoRA introduce weight updates without accounting for the spectral st

FusionSense: Tri-Stage Near-Sensor Learning for Runtime-Adaptive Multimodal Edge Intelligence

arXiv:2605.22868v1 Announce Type: new Abstract: Autonomous systems and smart-industry deployments increasingly split computation across near-sensor, edge, and cloud resources, where tight energy, late

agentsarxiv-cs-lg

GEMQ: Global Expert-Level Mixed-Precision Quantization for MoE LLMs

arXiv:2605.23078v1 Announce Type: cross Abstract: Mixture-of-Experts Large Language Models (MoE-LLMs) achieve strong performance but incur substantial memory overhead due to massive expert parameters.

researcharxiv-cs-cl

Geo-Align: Video Generation Alignment via Metric Geometry Reward

arXiv:2605.23903v1 Announce Type: new Abstract: Camera-controlled video generation has achieved remarkable progress in recent years. However, existing video-to-video re-rendering methods primarily rel

safetyarxiv-cs-cv

GFSR: Geometric Fidelity and Spatial Refinement for Reliable Lane Detection

arXiv:2605.23327v1 Announce Type: new Abstract: Lane detection stands as a crucial perception task in autonomous driving and advanced driver assistance systems. However, existing methods still degrade

agentsarxiv-cs-cv

GlyTwin: Digital Twin for Glucose Control in Type 1 Diabetes Through Optimal Behavioral Modifications Using Patient-Centric Counterfactuals

arXiv:2504.09846v2 Announce Type: replace-cross Abstract: Frequent and long-term exposure to hyperglycemia increases the risk of chronic complications, including neuropathy, nephropathy, and cardiovas

tutorialsarxiv-cs-ai

GMENet: Generative Mixture of Experts Network for Multi-Center Glioma Diagnosis with Incomplete Imaging Sequences

arXiv:2605.23183v1 Announce Type: cross Abstract: Contemporary glioma diagnosis integrates molecular features with histopathology to guide clinical decision-making. However, in clinical settings, dive

tutorialsarxiv-cs-cv

Good Token Hunting: A Hitchhiker's Guide to Token Selection for Visual Geometry Transformers

arXiv:2605.23892v1 Announce Type: cross Abstract: Visual geometry transformers have become powerful architectures for multi-view 3D reconstruction, enabling joint prediction of multiple 3D attributes

tutorialsarxiv-cs-ai

GradingAttack: Exposing Security Vulnerabilities in LLM Based Educational Grading Agents

arXiv:2602.00979v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly deployed as educational agents for automatic short answer grading (ASAG) in real-world education

Hardware

Graph Learning via Logic-Based Weisfeiler-Leman Variants and Tabularization

arXiv:2508.10651v3 Announce Type: replace Abstract: We present a novel approach for graph classification based on tabularizing graph data via new variants of the Weisfeiler-Leman algorithm and then ap

hardwarearxiv-cs-lg

HARNESS-LM: A Three-Phase Training Recipe for Harnessing SLMs in Sponsored Search Retrieval

arXiv:2605.23572v1 Announce Type: cross Abstract: In the competitive landscape of sponsored search, balancing retrieval quality with production latency is a critical challenge. While large retrieval m

Hinge Regression Trees and HRT-Boost: Newton-Optimized Oblique Learning for Compact Tabular Models

arXiv:2605.23422v1 Announce Type: new Abstract: Learning high-quality oblique decision trees remains a significant challenge due to the discrete and non-convex nature of split optimization. We present

applicationsarxiv-cs-lg

How Many Training Samples Are Needed for the Inverse Kinematics Solutions by Artificial Neural Networks

arXiv:2605.23583v1 Announce Type: cross Abstract: Inverse Kinematics (IK) plays a critical role in robotic motion planning and control. The IK solutions of a robot manipulator could be done by convent

applicationsarxiv-cs-lg

Human-in-the-Loop Multi-Agent Ventilator Decision Support with Contextual Bandit Preference Learning

arXiv:2605.23320v1 Announce Type: new Abstract: Ventilator decision support requires sequential decisions that track evolving physiology and disease trajectories while respecting safety boundaries and

ImProver 2: Iteratively Self-Improving LMs for Neurosymbolic Proof Optimization

arXiv:2605.22885v1 Announce Type: new Abstract: Formal mathematics libraries are rapidly expanding, creating a growing need to refactor verified proofs for maintainability and to improve training data

Inconsistency-aware Multimodal Schrodinger Bridge for Deepfake Localization

arXiv:2605.23113v1 Announce Type: new Abstract: Audio-visual deepfake localization demands interval-level outputs that serve as temporal evidence. Despite recent progress, symmetric fusion under singl

researcharxiv-cs-cv

InfiGFusion: Graph-on-Logits Distillation via Efficient Gromov-Wasserstein for Model Fusion

arXiv:2505.13893v2 Announce Type: replace Abstract: Recent advances in large language models (LLMs) have intensified efforts to fuse heterogeneous open-source models into a unified system that inherit

researcharxiv-cs-cl

Infra-Bayesian Reinforcement Learning Agents Outperform Classical RL For Worst-Case Robustness

arXiv:2605.23146v1 Announce Type: cross Abstract: Classical reinforcement learning assumes the agent interacts with a fixed environment whose behavior does not depend on the agent's policy. This assum

Joint Model Parameter Scaling and Universal-Domain Data Integration for E-commerce Search Ranking

model-releasesarxiv-cs-lg

arXiv:2603.24226v3 Announce Type: replace-cross Abstract: Scaling studies for industrial search, advertising, and recommendation have largely emphasized enlarging model capacity or refining architectu

JointHRRP-Net: A Statistically Constrained Decoupling Network for Joint Target and Jamming Recognition in Composite Jamming

arXiv:2605.22857v1 Announce Type: cross Abstract: High-resolution range profile (HRRP)-based radar automatic target recognition suffers from severe performance degradation in composite jamming environ

researcharxiv-cs-lg

L-FAME: Longitudinal Focused Attention Meditation EEG Dataset and Benchmark

model-releasesarxiv-cs-lg

arXiv:2605.22893v1 Announce Type: cross Abstract: We introduce a novel Longitudinal Focused Attention Meditation Electroencephalography (L-FAME) dataset and an accompanying benchmark, designed to fost

Label-Efficient Dataset Pruning via Semi-Supervised Pseudo-Labeling

arXiv:2605.23198v1 Announce Type: new Abstract: Dataset pruning reduces the storage and training costs of deep learning by selecting an informative subset from a large dataset. However, most existing

researcharxiv-cs-lg

LACY: A Vision-Language Model-based Language-Action Cycle for Self-Improving Robotic Manipulation

arXiv:2511.02239v2 Announce Type: replace-cross Abstract: Learning generalizable policies for robotic manipulation increasingly relies on large-scale models that map language instructions to actions (

Learned Relay Representations for Forward-Thinking Discrete Diffusion Models

arXiv:2605.22967v1 Announce Type: new Abstract: When Masked Diffusion Models (MDMs) generate sequences through iterative refinement, the rich internal computation over masked positions is discarded, f

tutorialsarxiv-cs-lg

Learning Individual Dynamics from Sparse Cross-Sectional Snapshots

arXiv:2605.23470v1 Announce Type: cross Abstract: Predicting how a dynamical unit evolves over time - how an individual ages, an epidemic spreads, or a physical system degrades - typically requires de

applicationsarxiv-cs-ai

LLM Sparsity Prior for Robust Feature Selection

arXiv:2605.23102v1 Announce Type: cross Abstract: Large language models (LLMs) offer a scalable mechanism to elicit domain-informed prior information for high-dimensional variable selection. However,

researcharxiv-cs-lg

LLMs as Noisy Channels: A Shannon Perspective on Model Capacity and Scaling Laws

arXiv:2605.23901v1 Announce Type: cross Abstract: Existing scaling laws for Large Language Models (LLMs), predominantly monotonic power laws, fail to explain emerging non-monotonic phenomena such as c

MadEvolve: Evolutionary Optimization of Trading Systems with Large Language Models

arXiv:2605.23007v1 Announce Type: cross Abstract: We explore the application of LLM-driven algorithm optimization to several common tasks in quantitative finance. MadEvolve, a general-purpose algorith

MAS-Orchestra: Understanding and Improving Multi-Agent Reasoning Through Holistic Orchestration and Controlled Benchmarks

arXiv:2601.14652v5 Announce Type: replace Abstract: While multi-agent systems (MAS) promise elevated intelligence through coordination of agents, current approaches to automatic MAS design under-deliv

MDS-DETR: DETR with Masked Duplicate Suppressor

arXiv:2605.23507v1 Announce Type: new Abstract: The DEtection TRansformer (DETR) is a powerful end-to-end object detector, yet its one-to-one matching strategy suffers from slow convergence and low re

researcharxiv-cs-cv

Mediative Fuzzy Logic: From Type-1 Foundations to Type-2, Type-3 and Quantum Extensions

arXiv:2605.22900v1 Announce Type: new Abstract: Mediative Fuzzy Logic was conceived as a practical scheme for reconciling hesitant or conflicting assessments in fuzzy control and decision-making. Howe

MedSAE: Dissecting MedCLIP Representations with Sparse Autoencoders

arXiv:2510.26411v2 Announce Type: replace Abstract: Artificial intelligence in healthcare requires models that are accurate and interpretable. We advance mechanistic interpretability in medical vision

applicationsarxiv-cs-ai

Metacognition as Reward: Reinforcing LLM Reasoning via Knowledge and Regulation Signals

arXiv:2605.23384v1 Announce Type: cross Abstract: Recent RL methods have substantially improved the reasoning abilities of LLMs. Existing reward designs mainly follow two paradigms: (1) Reinforcement

Millimeter-wave Imaging for Anthropometric Body Measurement

arXiv:2605.23064v1 Announce Type: new Abstract: Body shape and circumferences are clinically informative biomarkers for risk stratification, including measures such as waist to hip ratio, limb and tru

safetyarxiv-cs-cv

MirrorCheck: Efficient Adversarial Defense for Vision-Language Models

arXiv:2406.09250v3 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) are increasingly susceptible to sophisticated adversarial attacks, including adaptive strategies specifically de

Mitigating Object Hallucinations via Sentence-Level Early Intervention

arXiv:2507.12455v3 Announce Type: replace Abstract: Multimodal large language models (MLLMs) have revolutionized cross-modal understanding but continue to struggle with hallucinations - fabricated con

researcharxiv-cs-cv

Multi-Floor Exploration for Ground Robots via an Incremental Reachable Graph and Structural Priors

arXiv:2605.23350v1 Announce Type: new Abstract: Autonomous exploration of multi-floor buildings remains challenging for ground robots because conventional 2D and 2.5D maps cannot represent overlapping

agentsarxiv-cs-ro

Multi-SpatialMLLM: Multi-Frame Spatial Understanding with Multi-Modal Large Language Models

model-releasesarxiv-cs-cl

arXiv:2505.17015v2 Announce Type: replace-cross Abstract: Multi-modal large language models (MLLMs) have rapidly advanced in visual tasks, yet their spatial understanding remains limited to single ima

Multimodal Crystal Flow: Any-to-Any Modality Generation for Unified Crystal Modeling

arXiv:2602.20210v2 Announce Type: replace-cross Abstract: Crystal modeling spans a family of conditional and unconditional generation tasks, including crystal structure prediction (CSP) and de novo ge

Multimodal Distribution Matching for Vision-Language Dataset Distillation

arXiv:2605.23482v1 Announce Type: cross Abstract: Dataset distillation compresses large training sets into compact synthetic datasets while preserving downstream performance. As modern systems increas

NeuralBoneReg: An Instance-Specific Label-Free Point Cloud-Based Method for Multi-Modal Bone Surface Registration

arXiv:2511.14286v2 Announce Type: replace Abstract: In computer- and robot-assisted orthopedic surgery (CAOS), patient-specific surgical plans derived from preoperative imaging define target locations

safetyarxiv-cs-cv

NeuroWeaver: An Autonomous Evolutionary Agent for Exploring the Programmatic Space of EEG Analysis Pipelines

arXiv:2602.13473v2 Announce Type: replace Abstract: Although foundation models have demonstrated remarkable success in general domains, the application of these models to electroencephalography (EEG)

Tools

Notes on Pope Leo XIV's encyclical on AI

Dropped this morning by the Vatican: Magnifica Humanitas of His Holiness Pope Leo XIV on Safeguarding the Human Person in the Time of Artificial Intelligence. This is a very interesting document. It's

toolssimon-willison

NP-LoRA: Null Space Projection for Subject-Style LoRA Fusion

model-releasesarxiv-cs-cv

arXiv:2511.11051v3 Announce Type: replace Abstract: Low-Rank Adaptation (LoRA) fusion enables the composition of subject and style representations for controllable generation without retraining. Howev

On the Koopman-Based Generalization Bounds for Multi-Task Deep Learning

arXiv:2512.19199v2 Announce Type: replace-cross Abstract: The paper establishes generalization bounds for multitask deep neural networks using operator-theoretic techniques. The authors propose a tigh

On the Provable Importance of Gradients for Language-Assisted Image Clustering

arXiv:2510.16335v4 Announce Type: replace Abstract: This paper investigates the recently emerged problem of Language-assisted Image Clustering (LaIC), where textual semantics are leveraged to improve

tutorialsarxiv-cs-cv