Search: “papers”

Preventing Overfitting in Deep Image Prior for Hyperspectral Image Denoising

arXiv:2604.08272v1 Announce Type: new Abstract: Deep image prior (DIP) is an unsupervised deep learning framework that has been successfully applied to a variety of inverse imaging problems. However,

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ProofSketcher: Hybrid LLM + Lightweight Proof Checker for Reliable Math/Logic Reasoning

DGX agent

arXiv:2604.06401v1 Announce Type: new Abstract: The large language models (LLMs) might produce a persuasive argument within mathematical and logical fields, although such argument often includes some

researcharxiv-cs-ai

10 Apr 2026

Quantitative Estimation of Target Task Performance from Unsupervised Pretext Task in Semi/Self-Supervised Learning

arXiv:2508.07299v2 Announce Type: replace-cross Abstract: The effectiveness of unlabeled data in Semi/Self-Supervised Learning (SSL) depends on appropriate assumptions for specific scenarios, thereby

Quantum-Inspired Tensor Network Autoencoders for Anomaly Detection: A MERA-Based Approach

model-releasesarxiv-cs-lg

arXiv:2604.06541v1 Announce Type: cross Abstract: We investigate whether a multiscale tensor-network architecture can provide a useful inductive bias for reconstruction-based anomaly detection in coll

Tutorials

Reading Recognition in the Wild

arXiv:2505.24848v4 Announce Type: replace Abstract: To enable egocentric contextual AI in always-on smart glasses, it is crucial to be able to keep a record of the user's interactions with the world,

tutorialsarxiv-cs-cv

Reason in Chains, Learn in Trees: Self-Rectification and Grafting for Multi-turn Agent Policy Optimization

arXiv:2604.07165v1 Announce Type: new Abstract: Reinforcement learning for Large Language Model agents is often hindered by sparse rewards in multi-step reasoning tasks. Existing approaches like Group

safetyarxiv-cs-ai

RectifiedHR: Enable Efficient High-Resolution Synthesis via Energy Rectification

arXiv:2503.02537v4 Announce Type: replace Abstract: Diffusion models have achieved remarkable progress across various visual generation tasks. However, their performance significantly declines when ge

Rectifying LLM Thought from Lens of Optimization

arXiv:2512.01925v2 Announce Type: replace-cross Abstract: Recent advancements in large language models (LLMs) have been driven by their emergent reasoning capabilities, particularly through long chain

ReDAct: Uncertainty-Aware Deferral for LLM Agents

arXiv:2604.07036v1 Announce Type: cross Abstract: Recently, LLM-based agents have become increasingly popular across many applications, including complex sequential decision-making problems. However,

agentsarxiv-cs-lg

Resource-constrained Amazons chess decision framework integrating large language models and graph attention

arXiv:2603.10512v2 Announce Type: replace Abstract: Artificial intelligence has advanced significantly through the development of intelligent game-playing systems, providing rigorous testbeds for deci

Revisiting Radar Perception With Spectral Point Clouds

model-releasesarxiv-cs-cv

arXiv:2604.08282v1 Announce Type: new Abstract: Radar perception models are trained with different inputs, from range-Doppler spectra to sparse point clouds. Dense spectra are assumed to outperform sp

Hardware

RLBoost: Harvesting Preemptible Resources for Cost-Efficient Reinforcement Learning on LLMs

arXiv:2510.19225v3 Announce Type: replace-cross Abstract: Reinforcement learning (RL) has become essential for unlocking advanced reasoning capabilities in large language models (LLMs). RL workflows i

hardwarearxiv-cs-lg

Robust Multi-Agent Target Tracking in Intermittent Communication Environments via Analytical Belief Merging

arXiv:2604.07575v1 Announce Type: new Abstract: Autonomous multi-agent target tracking in GPS-denied and communication-restricted environments (e.g., underwater exploration, subterranean search and re

agentsarxiv-cs-ro

Scientific Knowledge-driven Decoding Constraints Improving the Reliability of LLMs

arXiv:2604.06603v1 Announce Type: cross Abstract: Large language models (LLMs) have shown strong knowledge reserves and task-solving capabilities, but still face the challenge of severe hallucination,

SD-FSMIS: Adapting Stable Diffusion for Few-Shot Medical Image Segmentation

arXiv:2604.03134v2 Announce Type: replace Abstract: Few-Shot Medical Image Segmentation (FSMIS) aims to segment novel object classes in medical images using only minimal annotated examples, addressing

Self-Distilled RLVR

arXiv:2604.03128v2 Announce Type: replace Abstract: On-policy distillation (OPD) has become a popular training paradigm in the LLM community. This paradigm selects a larger model as the teacher to pro

safetyarxiv-cs-lg

Local Ai

ShadowNPU: System and Algorithm Co-design for NPU-Centric On-Device LLM Inference

arXiv:2508.16703v4 Announce Type: replace-cross Abstract: On-device running Large Language Models (LLMs) is nowadays a critical enabler towards preserving user privacy. We observe that the attention o

local-aiarxiv-cs-ai

Smart Commander: A Hierarchical Reinforcement Learning Framework for Fleet-Level PHM Decision Optimization

arXiv:2604.07171v1 Announce Type: new Abstract: Decision-making in military aviation Prognostics and Health Management (PHM) faces significant challenges due to the 'curse of dimensionality' in large-

SpecQuant: Spectral Decomposition and Adaptive Truncation for Ultra-Low-Bit LLMs Quantization

arXiv:2511.11663v2 Announce Type: replace-cross Abstract: The emergence of accurate open large language models (LLMs) has sparked a push for advanced quantization techniques to enable efficient deploy

State and Trajectory Estimation of Tensegrity Robots via Factor Graphs and Chebyshev Polynomials

arXiv:2604.08185v1 Announce Type: new Abstract: Tensegrity robots offer compliance and adaptability, but their nonlinear, and underconstrained dynamics make state estimation challenging. Reliable cont

applicationsarxiv-cs-ro

Stop Listening to Me! How Multi-turn Conversations Can Degrade LLM Diagnostic Reasoning

arXiv:2603.11394v2 Announce Type: replace Abstract: Patients and clinicians are increasingly using chatbots powered by large language models (LLMs) for healthcare inquiries. While state-of-the-art LLM

applicationsarxiv-cs-cl

Syntax Is Easy, Semantics Is Hard: Evaluating LLMs for LTL Translation

arXiv:2604.07321v1 Announce Type: cross Abstract: Propositional Linear Temporal Logic (LTL) is a popular formalism for specifying desirable requirements and security and privacy policies for software,

Tabular GANs for uneven distribution

model-releasesarxiv-cs-cv

arXiv:2010.00638v2 Announce Type: replace-cross Abstract: Generative models for tabular data have evolved rapidly beyond Generative Adversarial Networks (GANs). While GANs pioneered synthetic tabular

TalkLoRA: Communication-Aware Mixture of Low-Rank Adaptation for Large Language Models

arXiv:2604.06291v1 Announce Type: cross Abstract: Low-Rank Adaptation (LoRA) enables parameter-efficient fine-tuning of Large Language Models (LLMs), and recent Mixture-of-Experts (MoE) extensions fur

TeaLeafVision: An Explainable and Robust Deep Learning Framework for Tea Leaf Disease Classification

arXiv:2604.07182v1 Announce Type: cross Abstract: As the worlds second most consumed beverage after water, tea is not just a cultural staple but a global economic force of profound scale and influence

applicationsarxiv-cs-ai

exttt{SEM-CTRL}: Semantically Controlled Decoding

arXiv:2503.01804v4 Announce Type: replace Abstract: Ensuring both syntactic and semantic correctness in Large Language Model (LLM) outputs remains a significant challenge, despite being critical for r

applicationsarxiv-cs-cl

The Art of Building Verifiers for Computer Use Agents

arXiv:2604.06240v1 Announce Type: cross Abstract: Verifying the success of computer use agent (CUA) trajectories is a critical challenge: without reliable verification, neither evaluation nor training

agentsarxiv-cs-ai

The Stepwise Informativeness Assumption: Why are Entropy Dynamics and Reasoning Correlated in LLMs?

arXiv:2604.06192v1 Announce Type: cross Abstract: Recent work uses entropy-based signals at multiple representation levels to study reasoning in large language models, but the field remains largely em

The Traveling Thief Problem with Time Windows: Benchmarks and Heuristics

arXiv:2604.06724v1 Announce Type: cross Abstract: While traditional optimization problems were often studied in isolation, many real-world problems today require interdependence among multiple optimiz

The Unreasonable Effectiveness of Data for Recommender Systems

arXiv:2604.06420v2 Announce Type: cross Abstract: In recommender systems, collecting, storing, and processing large-scale interaction data is increasingly costly in terms of time, energy, and computat

Tool Retrieval Bridge: Aligning Vague Instructions with Retriever Preferences via Bridge Model

model-releasesarxiv-cs-cl

arXiv:2604.07816v1 Announce Type: new Abstract: Tool learning has emerged as a promising paradigm for large language models (LLMs) to address real-world challenges. Due to the extensive and irregularl

Local Ai

Toward Personalized Darts Training: A Data-Driven Framework Based on Skeleton-Based Biomechanical Analysis and Motion Modeling

arXiv:2604.01130v3 Announce Type: replace Abstract: As sports training becomes more data-driven, traditional dart coaching based mainly on experience and visual observation is increasingly inadequate

local-aiarxiv-cs-lg

Towards Resilient Intrusion Detection in CubeSats: Challenges, TinyML Solutions, and Future Directions

arXiv:2604.06411v1 Announce Type: cross Abstract: CubeSats have revolutionized access to space by providing affordable and accessible platforms for research and education. However, their reliance on C

agentsarxiv-cs-ai

Towards Robust Content Watermarking Against Removal and Forgery Attacks

arXiv:2604.06662v1 Announce Type: cross Abstract: Generated contents have raised serious concerns about copyright protection, image provenance, and credit attribution. A potential solution for these p

Towards the Development of an LLM-Based Methodology for Automated Security Profiling in Compliance with Ukrainian Cybersecurity Regulations

arXiv:2604.06274v1 Announce Type: cross Abstract: In recent years, the pace of development of information technology in various areas has increased drastically, forcing cybersecurity specialists to co

safetyarxiv-cs-ai

TREASURE: The Visa Payment Foundation Model for High-Volume Transaction Understanding

arXiv:2511.19693v3 Announce Type: replace-cross Abstract: Payment networks form the backbone of modern commerce, generating high volumes of transaction records from daily activities. Properly modeling

applicationsarxiv-cs-ai

Uncertainty Estimation for Deep Reconstruction in Actuatic Disaster Scenarios with Autonomous Vehicles

arXiv:2604.06387v1 Announce Type: cross Abstract: Accurate reconstruction of environmental scalar fields from sparse onboard observations is essential for autonomous vehicles engaged in aquatic monito

agentsarxiv-cs-ai

Tutorials

Understanding Task Transfer in Vision-Language Models

arXiv:2511.18787v2 Announce Type: replace Abstract: Vision-Language Models (VLMs) perform well on multimodal benchmarks but lag behind humans and specialized models on visual perception tasks like dep

tutorialsarxiv-cs-cv

Verify Before You Commit: Towards Faithful Reasoning in LLM Agents via Self-Auditing

model-releasesarxiv-cs-cl

arXiv:2604.08401v1 Announce Type: cross Abstract: In large language model (LLM) agents, reasoning trajectories are treated as reliable internal beliefs for guiding actions and updating memory. However

ViVa: A Video-Generative Value Model for Robot Reinforcement Learning

arXiv:2604.08168v1 Announce Type: new Abstract: Vision-language-action (VLA) models have advanced robot manipulation through large-scale pretraining, but real-world deployment remains challenging due

safetyarxiv-cs-ro

Weakly-Supervised Lung Nodule Segmentation via Training-Free Guidance of 3D Rectified Flow

arXiv:2604.08313v1 Announce Type: new Abstract: Dense annotations, such as segmentation masks, are expensive and time-consuming to obtain, especially for 3D medical images where expert voxel-wise labe

Weaves, Wires, and Morphisms: Formalizing and Implementing the Algebra of Deep Learning

arXiv:2604.07242v1 Announce Type: new Abstract: Despite deep learning models running well-defined mathematical functions, we lack a formal mathematical framework for describing model architectures. Ad

Weight Group-wise Post-Training Quantization for Medical Foundation Model

arXiv:2604.07674v1 Announce Type: new Abstract: Foundation models have achieved remarkable results in medical image analysis. However, its large network architecture and high computational complexity

When Personalization Tricks Detectors: The Feature-Inversion Trap in Machine-Generated Text Detection

model-releasesarxiv-cs-cl

arXiv:2510.12476v2 Announce Type: replace Abstract: Large language models (LLMs) have grown more powerful in language generation, producing fluent text and even imitating personal style. Yet, this abi

'Why This Avoidance Maneuver?' Contrastive Explanations in Human-Supervised Maritime Autonomous Navigation

arXiv:2604.08032v1 Announce Type: cross Abstract: Automated maritime collision avoidance will rely on human supervision for the foreseeable future. This necessitates transparency into how the system p

agentsarxiv-cs-ro

Tutorials

https://x.com/ben_golub/status/2042079804271313343

tutorialsjeremy-howard--x

The specific tweet at that URL (status ID 2042079804271313343) could not be directly retrieved. However, based on the available context about Ben Golub's recent X/Twitter activity around Refine.ink...

9 Apr 2026

Is the ICML 2026 final justification period still open? [R]

researchr-machinelearning

The ICML 2026 'final justification' is a **new requirement this year** where reviewers must submit a written explanation of their final recommendation after reading author rebuttals. New for ICML ...

9 Apr 2026

// Scaling Coding Agents via Atomic Skills // Most coding agents train end-to-end on full tasks like resolving GitHub issues. But complex so…