All entries

Learning Tactile-Aware Quadrupedal Loco-Manipulation Policies

arXiv:2604.27224v1 Announce Type: new Abstract: Quadrupedal loco-manipulation is commonly built on visual perception and proprioception. Yet reliable contact-rich manipulation remains difficult: visio

safetyarxiv-cs-ro

Learning to Aggregate Zero-Shot LLM Agents for Corporate Disclosure Classification

DGX agent

arXiv:2603.20965v2 Announce Type: replace-cross Abstract: This paper studies whether a lightweight supervised aggregator can combine diverse zero-shot large language model outputs into a stronger down

researcharxiv-cs-ai

1 May 2026

Learning-to-Explain through 20Q Gaming: An Explainable Recommender for Cybersecurity Education

arXiv:2604.26964v1 Announce Type: cross Abstract: The growing sophistication of contemporary cyber threats necessitates a more effective and adaptive approach to cybersecurity training. Intuitive and

Learning to Forget: Continual Learning with Adaptive Weight Decay

arXiv:2604.27063v1 Announce Type: new Abstract: Continual learning agents with finite capacity must balance acquiring new knowledge with retaining the old. This requires controlled forgetting of knowl

Learning to Reason: Targeted Knowledge Discovery and Fuzzy Logic Update for Robust Image Recognition

arXiv:2604.27759v1 Announce Type: cross Abstract: Integrating domain knowledge into deep neural networks is a promising way to improve generalization. Existing methods either encode prior knowledge in

applicationsarxiv-cs-ai

Learning to Spend: Model Predictive Control for Budgeting under Non-Stationary Returns

arXiv:2604.27186v1 Announce Type: cross Abstract: We study finite-horizon budget allocation as a closed-loop economic control problem and evaluate receding-horizon Model Predictive Control (MPC) relat

researcharxiv-cs-ai

Learning When to Remember: Risk-Sensitive Contextual Bandits for Abstention-Aware Memory Retrieval in LLM-Based Coding Agents

arXiv:2604.27283v1 Announce Type: cross Abstract: Large language model (LLM)-based coding agents increasingly rely on external memory to reuse prior debugging experience, repair traces, and repository

Length Value Model: Scalable Value Pretraining for Token-Level Length Modeling

arXiv:2604.27039v1 Announce Type: new Abstract: Token serves as the fundamental unit of computation in modern autoregressive models, and generation length directly influences both inference cost and r

researcharxiv-cs-cl

Let's Measure Information Step-by-Step: AI-Based Evaluation Beyond Vibes

arXiv:2508.05469v3 Announce Type: replace Abstract: We evaluate artificial intelligence (AI) systems without ground truth by exploiting a link between strategic gaming and information loss. Building o

agentsarxiv-cs-lg

Leveraging Quantum-Based Architectures for Robust Diagnostics

arXiv:2511.12386v2 Announce Type: replace Abstract: Quantum machine learning has emerged as a promising approach for medical image analysis, particularly in settings where compact models and expressiv

researcharxiv-cs-cv

Leveraging Verifier-Based Reinforcement Learning in Image Editing

arXiv:2604.27505v1 Announce Type: new Abstract: While Reinforcement Learning from Human Feedback (RLHF) has become a pivotal paradigm for text-to-image generation, its application to image editing rem

researcharxiv-cs-cv

Lightweight Distillation of SAM 3 and DINOv3 for Edge-Deployable Individual-Level Livestock Monitoring and Longitudinal Visual Analytics

arXiv:2604.27128v1 Announce Type: cross Abstract: Foundation-model pipelines for individual-level livestock monitoring -- combining open-vocabulary detection, promptable video segmentation, and self-s

Limit Theorems for Stochastic Gradient Descent in High-Dimensional Single-Layer Networks

arXiv:2511.02258v2 Announce Type: replace-cross Abstract: This paper studies the high-dimensional scaling limits of online stochastic gradient descent (SGD). Building on the recent work of Ben Arous,

Linear-Core Surrogates: Smooth Loss Functions with Linear Rates for Classification and Structured Prediction

arXiv:2604.27742v1 Announce Type: new Abstract: The choice of loss function in classification involves a fundamental trade-off: smooth losses (like Cross-Entropy) enable fast optimization rates but yi

Linear Models, Variable Selection, Artificial Intelligence

arXiv:2604.27191v1 Announce Type: cross Abstract: Variable selection in linear regression models has been a problem since hypothesis testing began. Which variables to include or exclude from a model i

Linguistically Informed Multimodal Fusion for Vietnamese Scene-Text Image Captioning: Dataset, Graph Framework, and Phonological Attention

arXiv:2604.27712v1 Announce Type: cross Abstract: Scene-text image captioning requires fusing three information streams -- visual features, OCR-detected text, and linguistic knowledge -- to generate d

safetyarxiv-cs-cl

@llama_index should we rebrand to applied automation co.

Jerry Liu considers whether llama_index should rebrand to 'applied automation co,' suggesting potential strategic discussions about the project's direction and positioning. This appears to be a casual

agentsjerry-liu--x

LLM as Clinical Graph Structure Refiner: Enhancing Representation Learning in EEG Seizure Diagnosis

arXiv:2604.28178v1 Announce Type: new Abstract: Electroencephalogram (EEG) signals are vital for automated seizure detection, but their inherent noise makes robust representation learning challenging.

researcharxiv-cs-ai

LLM-based User Profile Management for Recommender System

arXiv:2502.14541v3 Announce Type: replace Abstract: The rapid advancement of Large Language Models (LLMs) has opened new opportunities in recommender systems by enabling zero-shot recommendation witho

applicationsarxiv-cs-cl

LLM Biases

arXiv:2604.26960v1 Announce Type: cross Abstract: Transformer-based agentic AI is rapidly being deployed on major platforms to help users shop, watch, and navigate content with less effort. While thes

LLM-Guided Runtime Parameter Optimization for Energy-Efficient Model Inference

arXiv:2604.27032v1 Announce Type: cross Abstract: Large Language Models (LLMs) have become an integral part of many real-world workflows. However, LLMs consume a lot of energy, which becomes a large c

LLMs as ASP Programmers: Self-Correction Enables Task-Agnostic Nonmonotonic Reasoning

arXiv:2604.27960v1 Announce Type: new Abstract: Recent large language models (LLMs) have achieved impressive reasoning milestones but continue to struggle with high computational costs, logical incons

researcharxiv-cs-ai

LLMs Capture Emotion Labels, Not Emotion Uncertainty: Distributional Analysis and Calibration of Human--LLM Judgment Gaps

arXiv:2604.27345v1 Announce Type: new Abstract: Human annotators frequently disagree on emotion labels, yet most evaluations of Large Language Model (LLM) emotion annotation collapse these judgments i

researcharxiv-cs-cl

LM-CartSeg: Automated Segmentation of Lateral and Medial Cartilage and Subchondral Bone for Radiomics Analysis

arXiv:2512.03449v3 Announce Type: replace Abstract: Background and Objective: Radiomics of knee MRI requires robust, anatomically meaningful regions of interest (ROIs) that jointly capture cartilage a

researcharxiv-cs-cv

Local AI is about to be competitive. I will do everything in my power to make it better than Claude desktop/claude code by end of year.

model-releasesclem-delangue--x

Clem Delangue expresses commitment to advancing local AI models to compete with Anthropic's Claude Desktop and Claude Code offerings by year-end. The statement suggests focus on improving local AI cap

Local Ai

Lora epochs access

local-air-stablediffusion

LoRA training epochs define how many times the training images are repeated during each training round, with increasing the epoch count intensifying training cycles. The optimal epoch varies between d

Lost in Space? Vision-Language Models Struggle with Relative Camera Pose Estimation

arXiv:2601.22228v2 Announce Type: replace-cross Abstract: We study whether vision-language models (VLMs) can solve relative camera pose estimation (RCPE) from image pairs, a direct test of multi-view

Low Rank Adaptation for Adversarial Perturbation

arXiv:2604.27487v1 Announce Type: new Abstract: Low-Rank Adaptation (LoRA), which leverages the insight that model updates typically reside in a low-dimensional space, has significantly improved the t

LUNA: LUT-Based Neural Architecture for Fast and Low-Cost Qubit Readout

arXiv:2512.07808v2 Announce Type: replace-cross Abstract: Qubit readout is a critical operation in quantum computing systems, which maps the analog response of qubits into discrete classical states. D

M-DaQ: Retrieving Samples with Multilingual Diversity and Quality for Instruction Fine-Tuning Datasets

model-releasesarxiv-cs-cl

arXiv:2509.15549v2 Announce Type: replace Abstract: Multilingual instruction fine-tuning (IFT) empowers large language models to generalize across diverse linguistic and cultural contexts; however, hi

Machine Collective Intelligence for Explainable Scientific Discovery

arXiv:2604.27297v1 Announce Type: new Abstract: Deriving governing equations from empirical observations is a longstanding challenge in science. Although artificial intelligence (AI) has demonstrated

agentsarxiv-cs-ai

Machine Unlearning for Class Removal through SISA-based Deep Neural Network Architectures

arXiv:2604.27804v1 Announce Type: new Abstract: The rapid proliferation of image generation models and other artificial intelligence (AI) systems has intensified concerns regarding data privacy and us

applicationsarxiv-cs-cv

MAEO: Multiobjective Animorphic Ensemble Optimization for Scalable Large-scale Engineering Applications

arXiv:2604.26973v1 Announce Type: cross Abstract: Multiobjective optimization remains challenging for many scientific and engineering problems due to the need to balance convergence, diversity, and co

Make sure to read the blog post for a detailed analysis of frontier model failure modes: https://arcprize.org/blog/arc-agi-3-gpt-5-5-opus-4-…

model-releasesfrancois-chollet--x

Francois Chollet shared a blog post analyzing failure modes of frontier AI models, specifically examining performance on the ARC (Abstraction and Reasoning Corpus) AGI benchmark with models including

Making Conformal Predictors Robust in Healthcare Settings: a Case Study on EEG Classification

arXiv:2602.19483v2 Announce Type: replace-cross Abstract: Quantifying uncertainty in clinical predictions is critical for high-stakes diagnosis tasks. Conformal prediction offers a principled approach

applicationsarxiv-cs-ai

Making Logic a First-Class Citizen in Generative ML for Networking

arXiv:2506.23964v3 Announce Type: replace-cross Abstract: Generative ML models are increasingly popular in networking for tasks such as telemetry imputation, prediction, and synthetic trace generation

applicationsarxiv-cs-lg

Industry

Man dies covered in necrotic lesions after amoebas eat him alive

A 78-year-old man with a 6-month history of progressive skin lesions developed the condition after returning from Florida. The case was diagnosed as disseminated Acanthamoeba infection through PCR tes

industryars-technica

Man, Machine, and Mathematics

arXiv:2604.27052v1 Announce Type: cross Abstract: Nonlinear models and optimization methods have successfully tackled a rapidly growing set of problems in recent years. Indeed, a relatively small tool

many sensitive Agent Workloads today require some sort of human feedback LangGraph supplies the runtime primitives for LangChain + Deep Agen…

many sensitive Agent Workloads today require some sort of human feedback LangGraph supplies the runtime primitives for LangChain + Deep Agents and makes it easy to durably pause, resume, and replay ag

agentsharrison-chase--x

Mapping how LLMs debate societal issues when shadowing human personality traits, sociodemographics and social media behavior

arXiv:2604.27624v1 Announce Type: cross Abstract: Large Language Models (LLMs) can strongly shape social discourse, yet datasets investigating how LLM outputs vary across controlled social and context

Tutorials

Mapping the Methodological Space of Classroom Interaction Research: Scale, Duration, and Modality in an Age of AI

arXiv:2604.28098v1 Announce Type: new Abstract: Research on classroom interaction has long been divided between large-scale observation and in-depth ethnographic work. We propose a framework mapping t

tutorialsarxiv-cs-ai

Mapping the Phase Diagram of the Vicsek Model with Machine Learning

arXiv:2604.28167v1 Announce Type: cross Abstract: In this study, we use machine learning to classify and interpolate the phase structure of the Vicsek flocking model across the three-dimensional param

“Marcus’ specific point about coding is structurally important: a model that produces code which compiles and passes the tests it was given …

“Marcus’ specific point about coding is structurally important: a model that produces code which compiles and passes the tests it was given is not the same as a model that produces correct, secure, ma

safetygary-marcus--x

Hardware

Marketing Architects Scales Real-Time CTV Advertising with Vultr Infrastructure

Discover how Marketing Architects scaled real-time CTV advertising with Vultr, doubling throughput, reducing latency by 50%, and cutting cloud costs by up to 50% with high-performance Kubernetes and c

hardwarevultr

Hardware

MARS: Efficient, Adaptive Co-Scheduling for Heterogeneous Agentic Systems

arXiv:2604.26963v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as the execution core of autonomous agents rather than as standalone text generators. Agentic w

hardwarearxiv-cs-lg

Math Education Digital Shadows for facilitating learning with LLMs: Math performance, anxiety and confidence in simulated students and AIs

arXiv:2604.27618v1 Announce Type: new Abstract: To enhance LLMs' impact on math education, we need data on their mathematical prowess and biases across prompts. To fill this gap, we introduce MEDS (Ma

MCP vs. CLI Skills for agents: what our eval found (and which you should use)

Twitter said pick a side. The eval said the question was wrong. Six months ago, MCP (model context protocol) was the hot new thing: tool usage with a built-in discovery... The post MCP vs. CLI Skills

agentsarize-ai

MCPHunt: An Evaluation Framework for Cross-Boundary Data Propagation in Multi-Server MCP Agents

arXiv:2604.27819v1 Announce Type: new Abstract: Multi-server MCP agents create an information-flow control problem: faithful tool composition can turn individually benign read/write permissions into c