Search: “framework”

Improving LLM Unlearning Robustness via Random Perturbations

arXiv:2501.19202v5 Announce Type: replace Abstract: Here, we show that current LLM unlearning methods inherently reduce models' robustness, causing them to misbehave even when a single non-adversarial

researcharxiv-cs-cl

Inertial Magnetic SLAM Systems Using Low-Cost Sensors

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

DGX agent

arXiv:2512.10128v2 Announce Type: replace Abstract: Spatially inhomogeneous magnetic fields offer a valuable, non-visual information source for positioning. Among systems leveraging this, magnetic fie

local-aiarxiv-cs-ro

14 Apr 2026

Inside the Scaffold: A Source-Code Taxonomy of Coding Agent Architectures

arXiv:2604.03515v2 Announce Type: replace-cross Abstract: LLM-based coding agents can localize bugs, generate patches, and run tests with diminishing human oversight, yet the scaffolding code that sur

local-aiarxiv-cs-ai

Introduction to Automated Negotiation

arXiv:2511.08659v3 Announce Type: replace-cross Abstract: This book is an introductory textbook targeted towards computer science students who are completely new to the topic of automated negotiation.

Learning to Focus: CSI-Free Hierarchical MARL for Reconfigurable Reflectors

arXiv:2604.05165v2 Announce Type: replace Abstract: Reconfigurable Intelligent Surfaces (RIS) has a potential to engineer smart radio environments for next-generation millimeter-wave (mmWave) networks

Learning Visually Interpretable Oscillator Networks for Soft Continuum Robots from Video

arXiv:2511.18322v3 Announce Type: replace-cross Abstract: Learning soft continuum robot (SCR) dynamics from video offers flexibility but existing methods lack interpretability or rely on prior assumpt

researcharxiv-cs-cv

Learning What's Real: Disentangling Signal and Measurement Artifacts in Multi-Sensor Data, with Applications to Astrophysics

model-releasesarxiv-cs-lg

arXiv:2604.09787v1 Announce Type: cross Abstract: Data collected from the physical world is always a combination of multiple sources: an underlying signal from the physical process of interest and a s

LETGAMES: An LLM-Powered Gamified Approach to Cognitive Training for Patients with Cognitive Impairment

arXiv:2604.09566v1 Announce Type: cross Abstract: The application of games as a therapeutic tool for cognitive training is beneficial for patients with cognitive impairments. However, effective game d

Applications

Leveraging Machine Learning Techniques to Investigate Media and Information Literacy Competence in Tackling Disinformation

arXiv:2604.09635v1 Announce Type: cross Abstract: This study develops machine learning models to assess Media and Information Literacy (MIL) skills specifically in the context of disinformation among

applicationsarxiv-cs-ai

Linear Attention Based Deep Nonlocal Means Filtering for Multiplicative Noise Removal

arXiv:2407.05087v2 Announce Type: replace-cross Abstract: Multiplicative noise widely exists in radar images, medical images and other important fields' images. Compared to normal noises, multiplicati

Tutorials

LitPivot: Developing Well-Situated Research Ideas Through Dynamic Contextualization and Critique within the Literature Landscape

arXiv:2604.02600v2 Announce Type: replace-cross Abstract: Developing a novel research idea is hard. It must be distinct enough from prior work to claim a contribution while also building on it. This r

tutorialsarxiv-cs-ai

LPNSR: Optimal Noise-Guided Diffusion Image Super-Resolution Via Learnable Noise Prediction

arXiv:2603.21045v4 Announce Type: replace-cross Abstract: Diffusion-based image super-resolution (SR) aims to reconstruct high-resolution (HR) images from low-resolution (LR) observations, yet faces a

M^{2}SNet: Multi-scale in Multi-scale Subtraction Network for Medical Image Segmentation

arXiv:2303.10894v3 Announce Type: replace Abstract: Accurate medical image segmentation is critical for early medical diagnosis. Most existing methods are based on U-shape structure and use element-wi

researcharxiv-cs-cv

MASS: Motion-Aware Spatial-Temporal Grounding for Physics Reasoning and Comprehension in Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2511.18373v2 Announce Type: replace Abstract: Vision Language Models (VLMs) perform well on standard video tasks but struggle with physics-related reasoning involving motion dynamics and spatial

MAVEN-T: Multi-Agent enVironment-aware Enhanced Neural Trajectory predictor with Reinforcement Learning

model-releasesarxiv-cs-ai

arXiv:2604.10169v1 Announce Type: new Abstract: Trajectory prediction remains a critical yet challenging component in autonomous driving systems, requiring sophisticated reasoning capabilities while m

MegaFake: A Theory-Driven Dataset of Fake News Generated by Large Language Models

arXiv:2408.11871v4 Announce Type: replace-cross Abstract: Fake news significantly influences decision-making processes by misleading individuals, organizations, and even governments. Large language mo

Mem^2Evolve: Towards Self-Evolving Agents via Co-Evolutionary Capability Expansion and Experience Distillation

arXiv:2604.10923v1 Announce Type: cross Abstract: While large language model--powered agents can self-evolve by accumulating experience or by dynamically creating new assets (i.e., tools or expert age

MERMAID: Memory-Enhanced Retrieval and Reasoning with Multi-Agent Iterative Knowledge Grounding for Veracity Assessment

model-releasesarxiv-cs-ai

arXiv:2601.22361v2 Announce Type: replace-cross Abstract: Assessing the veracity of online content has become increasingly critical. Large language models (LLMs) have recently enabled substantial prog

METRO: Towards Strategy Induction from Expert Dialogue Transcripts for Non-collaborative Dialogues

arXiv:2604.11427v1 Announce Type: cross Abstract: Developing non-collaborative dialogue agents traditionally requires the manual, unscalable codification of expert strategies. We propose ours, a metho

Minimal Embodiment Enables Efficient Learning of Number Concepts in Robot

arXiv:2604.11373v1 Announce Type: cross Abstract: Robots are increasingly entering human-interactive scenarios that require understanding of quantity. How intelligent systems acquire abstract numerica

Multidata Causal Discovery for Statistical Hurricane Intensity Forecasting

arXiv:2510.02050v3 Announce Type: replace-cross Abstract: Improving statistical forecasts of tropical cyclone (TC) intensity is limited by complex nonlinear interactions and difficulty in identifying

researcharxiv-cs-lg

Neuro-Symbolic Strong-AI Robots with Closed Knowledge Assumption: Learning and Deductions

arXiv:2604.09567v1 Announce Type: cross Abstract: Knowledge representation formalisms are aimed to represent general conceptual information and are typically used in the construction of the knowledge

No agent maintained moral reasoning consistency across scenarios. Findings from a structured study with 11 agents on classic ethical dilemmas [R]

No agent maintained moral reasoning consistency across scenarios. Findings from a structured study with 11 agents on classic ethical dilemmas [R]

agentsr-machinelearning

ODUTQA-MDC: A Task for Open-Domain Underspecified Tabular QA with Multi-turn Dialogue-based Clarification

model-releasesarxiv-cs-cl

arXiv:2604.10159v1 Announce Type: new Abstract: The advancement of large language models (LLMs) has enhanced tabular question answering (Tabular QA), yet they struggle with open-domain queries exhibit

One-Step Score-Based Density Ratio Estimation

arXiv:2604.10672v1 Announce Type: cross Abstract: Density ratio estimation (DRE) is a useful tool for quantifying discrepancies between probability distributions, but existing approaches often involve

researcharxiv-cs-lg

OpeFlo: Automated UX Evaluation via Simulated Human Web Interaction with GUI Grounding

arXiv:2604.09581v1 Announce Type: new Abstract: Evaluating web usability typically requires time-consuming user studies and expert reviews, which often limits iteration speed during product developmen

Optimization-Guided Diffusion for Interactive Scene Generation

arXiv:2512.07661v3 Announce Type: replace Abstract: Realistic and diverse multi-agent driving scenes are crucial for evaluating autonomous vehicles, but safety-critical events which are essential for

safetyarxiv-cs-cv

Hardware

PA-SFM: Tracker-free differentiable acoustic radiation for freehand 3D photoacoustic imaging

arXiv:2604.09643v1 Announce Type: new Abstract: Three-dimensional (3D) handheld photoacoustic tomography typically relies on bulky and expensive external positioning sensors to correct motion artifact

hardwarearxiv-cs-cv

PACO: Proxy-Task Alignment and Online Calibration for On-the-Fly Category Discovery

arXiv:2604.11484v1 Announce Type: new Abstract: On-the-Fly Category Discovery (OCD) requires a model, trained on an offline support set, to recognize known classes while discovering new ones from an o

safetyarxiv-cs-cv

Applications

PnP-CM: Consistency Models as Plug-and-Play Priors for Inverse Problems

arXiv:2509.22736v2 Announce Type: replace-cross Abstract: Diffusion models have found extensive use in solving inverse problems, by sampling from an approximate posterior distribution of data given th

applicationsarxiv-cs-ai

Post-Processing Methods for Improving Accuracy in MRI Inpainting

arXiv:2510.15282v2 Announce Type: replace-cross Abstract: Magnetic Resonance Imaging (MRI) is the primary imaging modality used in the diagnosis, assessment, and treatment planning for brain pathologi

local-aiarxiv-cs-ai

PrefPaint: Enhancing Medical Image Inpainting through Expert Human Feedback

arXiv:2506.21834v2 Announce Type: replace Abstract: Inpainting, the process of filling missing or corrupted image parts, has broad applications in medical imaging. However, generating anatomically acc

researcharxiv-cs-cv

PRIX: Learning to Plan from Raw Pixels for End-to-End Autonomous Driving

arXiv:2507.17596v3 Announce Type: replace-cross Abstract: While end-to-end autonomous driving models show promising results, their practical deployment is often hindered by large model sizes, a relian

Tutorials

Probabilistic Prediction of Neural Dynamics via Autoregressive Flow Matching

arXiv:2604.11178v1 Announce Type: cross Abstract: Forecasting neural activity in response to naturalistic stimuli remains a key challenge for understanding brain dynamics and enabling downstream neuro

tutorialsarxiv-cs-lg

Pseudo-Unification: Entropy Probing Reveals Divergent Information Patterns in Unified Multimodal Models

arXiv:2604.10949v1 Announce Type: cross Abstract: Unified multimodal models (UMMs) were designed to combine the reasoning ability of large language models (LLMs) with the generation capability of visi

RealSR-R1: Reinforcement Learning for Real-World Image Super-Resolution with Vision-Language Chain-of-Thought

arXiv:2506.16796v4 Announce Type: replace Abstract: Real-World Image Super-Resolution is one of the most challenging task in image restoration. However, existing methods struggle with an accurate unde

safetyarxiv-cs-cv

Reasoning as Gradient: Scaling MLE Agents Beyond Tree Search

model-releasesarxiv-cs-ai

arXiv:2603.01692v3 Announce Type: replace-cross Abstract: LLM-based agents for machine learning engineering (MLE) predominantly rely on tree search, a form of gradient-free optimization that uses scal

Regional Explanations: Bridging Local and Global Variable Importance

arXiv:2604.11223v1 Announce Type: cross Abstract: We analyze two widely used local attribution methods, Local Shapley Values and LIME, which aim to quantify the contribution of a feature value x_i to

local-aiarxiv-cs-ai

Hardware

Relational Probing: LM-to-Graph Adaptation for Financial Prediction

arXiv:2604.10212v1 Announce Type: new Abstract: Language models can be used to identify relationships between financial entities in text. However, while structured output mechanisms exist, prompting-b

hardwarearxiv-cs-cl

Resilient Write: A Six-Layer Durable Write Surface for LLM Coding Agents

arXiv:2604.10842v1 Announce Type: cross Abstract: LLM-powered coding agents increasingly rely on tool-use protocols such as the Model Context Protocol~(MCP) to read and write files on a developer's wo

Rethinking the Diffusion Model from a Langevin Perspective

arXiv:2604.10465v1 Announce Type: cross Abstract: Diffusion models are often introduced from multiple perspectives, such as VAEs, score matching, or flow matching, accompanied by dense and technically

Retrieval Is Not Enough: Why Organizational AI Needs Epistemic Infrastructure

arXiv:2604.11759v1 Announce Type: new Abstract: Organizational knowledge used by AI agents typically lacks epistemic structure: retrieval systems surface semantically relevant content without distingu

Saar-Voice: A Multi-Speaker Saarbrucken Dialect Speech Corpus

arXiv:2604.11803v1 Announce Type: new Abstract: Natural language processing (NLP) and speech technologies have made significant progress in recent years; however, they remain largely focused on standa

local-aiarxiv-cs-cl

Seg2Change: Adapting Open-Vocabulary Semantic Segmentation Model for Remote Sensing Change Detection

model-releasesarxiv-cs-cv

arXiv:2604.11231v1 Announce Type: new Abstract: Change detection is a fundamental task in remote sensing, aiming to quantify the impacts of human activities and ecological dynamics on land-cover chang

Self-Evolving LLM Memory Extraction Across Heterogeneous Tasks

model-releasesarxiv-cs-cl

arXiv:2604.11610v1 Announce Type: new Abstract: As LLM-based assistants become persistent and personalized, they must extract and retain useful information from past conversations as memory. However,

Semantic Segmentation Algorithm Based on Light Field and LiDAR Fusion

arXiv:2510.06687v2 Announce Type: replace-cross Abstract: Semantic segmentation serves as a cornerstone of scene understanding in autonomous driving but continues to face significant challenges under

Sheaf Diffusion with Adaptive Local Structure for Spatio-Temporal Forecasting

arXiv:2604.11275v1 Announce Type: new Abstract: Spatio-temporal systems often exhibit highly heterogeneous and non-intuitive responses to localized disruptions, limiting the effectiveness of conventio

local-aiarxiv-cs-lg

SkVM: Revisiting Language VM for Skills across Heterogenous LLMs and Harnesses

arXiv:2604.03088v3 Announce Type: replace-cross Abstract: LLM agents increasingly adopt skills as a reusable unit of composition. While skills are shared across diverse agent platforms, current system

agentsarxiv-cs-lg