All entries

LLM-Based Robustness Testing of Microservice Applications: An Empirical Study

arXiv:2605.14202v1 Announce Type: cross Abstract: Malformed, missing, or boundary-value inputs in microservice APIs can cascade across dependent services, threatening reliability. Robustness testing s

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

LLMs Know When They Know, but Do Not Act on It: A Metacognitive Harness for Test-time Scaling

DGX agent

arXiv:2605.14186v1 Announce Type: new Abstract: Large language models (LLMs) often expose useful signals of self-monitoring: before solving a problem, they can estimate whether they are likely to succ

model-releasesarxiv-cs-lg

15 May 2026

Tutorials

LLMs learn scientific taste from institutional traces across the social sciences

arXiv:2603.16659v3 Announce Type: replace Abstract: Reinforcement-learned reasoning has powered recent AI leaps on verifiable tasks, including mathematics, code, and structure prediction. The harder b

tutorialsarxiv-cs-ai

LLMs Should Express Uncertainty Explicitly

arXiv:2604.05306v2 Announce Type: replace-cross Abstract: Large language models (LLMs) often produce confident yet incorrect answers, which can lead to risky failures in real-world applications. We st

Tutorials

Local Spatiotemporal Convolutional Network for Robust Gait Recognition

arXiv:2605.14548v1 Announce Type: new Abstract: Gait recognition, as a promising biometric technology, identifies individuals through their unique walking patterns and offers distinctive advantages in

tutorialsarxiv-cs-cv

Logging Policy Design for Off-Policy Evaluation

arXiv:2605.15108v1 Announce Type: cross Abstract: Off-policy evaluation (OPE) estimates the value of a target treatment policy (e.g., a recommender system) using data collected by a different logging

safetyarxiv-cs-ai

LoMETab: Beyond Rank-1 Ensembles for Tabular Deep Learning

arXiv:2605.14365v1 Announce Type: cross Abstract: Recent tabular learning benchmarks increasingly show a tight performance cluster rather than a clear hierarchy among leading methods, spanning gradien

LoRA in LoRA: Towards Parameter-Efficient Architecture Expansion for Continual Visual Instruction Tuning

arXiv:2508.06202v2 Announce Type: replace-cross Abstract: Continual Visual Instruction Tuning (CVIT) enables Multimodal Large Language Models (MLLMs) to incrementally learn new tasks over time. Howeve

LoRIF: Low-Rank Influence Functions for Scalable Training Data Attribution

arXiv:2601.21929v2 Announce Type: replace Abstract: Training data attribution (TDA) identifies which training examples most influenced a model's prediction. Influence function methods are a theoretica

researcharxiv-cs-lg

LoVeC: Reinforcement Learning for Better Verbalized Confidence in Long-Form Generations

arXiv:2505.23912v2 Announce Type: replace-cross Abstract: Hallucination remains a major challenge for the safe and trustworthy deployment of large language models (LLMs) in factual content generation.

LPH-VTON: Resolving the Structure-Texture Dilemma of Virtual Try-On via Latent Process Handover

arXiv:2605.14874v1 Announce Type: new Abstract: Virtual Try-On (VTON) aims to synthesize photorealistic images of garments precisely aligned with a person's body and pose. Current diffusion-based meth

safetyarxiv-cs-cv

M^2RNN: Non-Linear RNNs with Matrix-Valued States for Scalable Language Modeling

arXiv:2603.14360v2 Announce Type: replace-cross Abstract: Transformers are highly parallel but are limited to computations in the TC^0 complexity class, excluding tasks such as entity tracking and cod

MahaVar: OOD Detection via Class-wise Mahalanobis Distance Variance under Neural Collapse

arXiv:2605.14413v1 Announce Type: cross Abstract: Out-of-distribution (OOD) detection is a critical component for ensuring the reliability of deep neural networks in safety-critical applications. In t

MALLVI: A Multi-Agent Framework for Integrated Generalized Robotics Manipulation

arXiv:2602.16898v5 Announce Type: replace-cross Abstract: Task planning for robotic manipulation with large language models (LLMs) is an emerging area. Prior approaches rely on specialized models, fin

MambaRain: Multi-Scale Mamba-Attention Framework for 0-3 Hour Precipitation Nowcasting

arXiv:2605.14606v1 Announce Type: new Abstract: Accurate precipitation nowcasting over extended horizons (0-3 hours) is essential for disaster mitigation and operational decision-making, yet remains a

researcharxiv-cs-cv

Applications

Manifold Dimension Estimation via Local Graph Structure

arXiv:2510.15141v4 Announce Type: replace-cross Abstract: Most existing manifold dimension estimators rely on the assumption that the underlying manifold is locally flat within the neighborhoods under

applicationsarxiv-cs-lg

MAPLE: Latent Multi-Agent Play for End-to-End Autonomous Driving

arXiv:2605.14201v1 Announce Type: cross Abstract: Vision-language-action (VLA) models are effective as end-to-end motion planners, but can be brittle when evaluated in closed-loop settings due to bein

safetyarxiv-cs-cv

MAPLE: Self-Supervised Learning-Enhanced Nonlinear Dimensionality Reduction for Visual Analysis

arXiv:2601.20173v2 Announce Type: replace Abstract: We present a new nonlinear dimensionality reduction method, MAPLE, that enhances UMAP by improving manifold modeling. MAPLE employs a self-supervise

researcharxiv-cs-lg

Applications

Masked Autoencoders with Limited Data: Does It Work? A Fine-Grained Bioacoustics Case Study

arXiv:2605.14031v1 Announce Type: cross Abstract: Bioacoustic recognition requires fine-grained acoustic understanding to distinguish similar-sounding species. However, many large-scale data repositor

applicationsarxiv-cs-cv

Masked Next-Scale Prediction for Self-supervised Scene Text Recognition

model-releasesarxiv-cs-cv

arXiv:2605.14885v1 Announce Type: new Abstract: Scene Text Recognition requires modeling visual structures that evolve from coarse layouts to fine-grained character strokes. Training such models relie

MathAtlas: A Benchmark for Autoformalization in the Wild

arXiv:2605.14061v1 Announce Type: new Abstract: Current autoformalization benchmarks are largely focused on olympiad or undergraduate mathematics, while graduate and research-level mathematics remains

Local Ai

Matrix-Space Reinforcement Learning for Reusing Local Transition Geometry

arXiv:2605.14304v1 Announce Type: cross Abstract: Compositional generalization in sequential decision-making requires identifying which parts of prior rollouts remain useful for new tasks. Existing me

local-aiarxiv-cs-ai

MD-PNOP: Equation-Recast Neural Operators for Minimal-Data Extrapolation and PDE Solver Acceleration

model-releasesarxiv-cs-lg

arXiv:2509.01416v2 Announce Type: replace Abstract: The computational overhead of traditional numerical solvers for partial differential equations (PDEs) remains a critical bottleneck for large-scale

Measuring and Mitigating Toxicity in Large Language Models: A Comprehensive Replication Study

arXiv:2605.14087v1 Announce Type: new Abstract: Large Language Models (LLMs), when trained on web-scale corpora, inherently absorb toxic patterns from their training data. This leads to ``toxic degene

safetyarxiv-cs-cl

Measuring Google AI Overviews: Activation, Source Quality, Claim Fidelity, and Publisher Impact

arXiv:2605.14021v1 Announce Type: cross Abstract: Google AI Overviews (AIOs) are arguably the most widely encountered deployment of generative AI, reaching over 2 billion users who may not realize the

Mechanical Enforcement for LLM Governance:Evidence of Governance-Task Decoupling in Financial Decision Systems

arXiv:2605.14744v1 Announce Type: cross Abstract: Large language models in regulated financial workflows are governed by natural-language policies that the same model interprets, creating a principal-

safetyarxiv-cs-ai

Mechanistic Interpretability of EEG Foundation Models via Sparse Autoencoders

model-releasesarxiv-cs-lg

arXiv:2605.13930v1 Announce Type: new Abstract: EEG foundation models achieve state-of-the-art clinical performance, yet the internal computations driving their predictions remain opaque: a barrier to

MechVerse: Evaluating Physical Motion Consistency in Video Generation Models

model-releasesarxiv-cs-cv

arXiv:2605.14843v1 Announce Type: new Abstract: Text- and image-conditioned video generation models have achieved strong visual fidelity and temporal coherence, but they often fail to generate motion

Med-DisSeg: Dispersion-Driven Representation Learning for Fine-Grained Medical Image Segmentation

arXiv:2605.14579v1 Announce Type: new Abstract: Accurate medical image segmentation is fundamental to precision medicine, yet robust delineation remains challenging under heterogeneous appearances, am

researcharxiv-cs-cv

MediaClaw: Multimodal Intelligent-Agent Platform Technical Report

arXiv:2605.14771v1 Announce Type: new Abstract: MediaClaw is a multimodal agent platform built on the OpenClaw ecosystem. Its core design follows a three-layer architecture of unified abstraction, plu

Medical Report Generation: A Hierarchical Task Structure-Based Cross-Modal Causal Intervention Framework

arXiv:2511.02271v2 Announce Type: replace Abstract: Medical Report Generation (MRG) is a key part of modern medical diagnostics, as it automatically generates reports from radiological images to reduc

safetyarxiv-cs-cv

MemEye: A Visual-Centric Evaluation Framework for Multimodal Agent Memory

arXiv:2605.15128v1 Announce Type: cross Abstract: Long-term agent memory is increasingly multimodal, yet existing evaluations rarely test whether agents preserve the visual evidence needed for later r

MemLens: Benchmarking Multimodal Long-Term Memory in Large Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2605.14906v1 Announce Type: new Abstract: Memory is essential for large vision-language models (LVLMs) to handle long, multimodal interactions, with two method directions providing this capabili

MemLineage: Lineage-Guided Enforcement for LLM Agent Memory

arXiv:2605.14421v1 Announce Type: cross Abstract: We introduce MemLineage, a defense for LLM agent memory that attaches both cryptographic provenance and LLM-mediated derivation lineage to every entry

Applications

MeMo: Memory as a Model

arXiv:2605.15156v1 Announce Type: cross Abstract: Large language models (LLMs) achieve strong performance across a wide range of tasks, but remain frozen after pretraining until subsequent updates. Ma

applicationsarxiv-cs-ai

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

MemReranker: Reasoning-Aware Reranking for Agent Memory Retrieval

arXiv:2605.06132v2 Announce Type: replace Abstract: In agent memory systems, the reranking model serves as the critical bridge connecting user queries with long-term memory. Most systems adopt the 're

Merging Methods for Multilingual Knowledge Editing for Large Language Models: An Empirical Odyssey

arXiv:2605.13919v1 Announce Type: new Abstract: Multilingual knowledge editing (MKE) remains challenging because language-specific edits interfere with one another, even when locate-then-edit methods

Meschers: Geometry Processing of Impossible Objects

arXiv:2605.14960v1 Announce Type: cross Abstract: Impossible objects, geometric constructions that humans can perceive but that cannot exist in real life, have been a topic of intrigue in visual arts,

researcharxiv-cs-cv

MetaAgent-X : Breaking the Ceiling of Automatic Multi-Agent Systems via End-to-End Reinforcement Learning

arXiv:2605.14212v1 Announce Type: new Abstract: Automatic multi-agent systems aim to instantiate agent workflows without relying on manually designed or fixed orchestration. However, existing automati

MetaBackdoor: Exploiting Positional Encoding as a Backdoor Attack Surface in LLMs

arXiv:2605.15172v1 Announce Type: cross Abstract: Backdoor attacks pose a serious security threat to large language models (LLMs), which are increasingly deployed as general-purpose assistants in safe

safetyarxiv-cs-cl

MetaMoE: Diversity-Aware Proxy Selection for Privacy-Preserving Mixture-of-Experts Unification

arXiv:2605.14289v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) models scale capacity by combining specialized experts, but most existing approaches assume centralized access to training da

Metis AI: The Overlooked Middle Zone Between AI-Native and World-Movers

arXiv:2605.14407v1 Announce Type: new Abstract: The dominant discourse on AI limitations frames the boundary of AI capability as a divide between digital tasks (where AI excels) and physical tasks (wh

MHSA: A Lightweight Framework for Mitigating Hallucinations via Steered Attention in LVLMs

arXiv:2605.14966v1 Announce Type: cross Abstract: Large vision-language models (LVLMs) have achieved remarkable performance across diverse multimodal tasks, yet they continue to suffer from hallucinat

MicroscopyMatching: Towards a Ready-to-use Framework for Microscopy Image Analysis in Diverse Conditions

arXiv:2605.14980v1 Announce Type: cross Abstract: Analyzing microscopy images to extract biological object properties (e.g., their morphological organization, temporal dynamics, and population density

MIMIC-D: Multi-modal Imitation for MultI-agent Coordination with Decentralized Diffusion Policies

arXiv:2509.14159v3 Announce Type: replace Abstract: As robots become more integrated in society, their ability to coordinate with other robots and humans on multi-modal tasks (those with multiple vali

agentsarxiv-cs-ro

Local Ai

MindGap: A Conversational AI Framework for Upstream Neuroplastic Intervention in Post-Traumatic Stress Disorder

arXiv:2605.14660v1 Announce Type: new Abstract: Post-Traumatic Stress Disorder (PTSD) is fundamentally a neuroplastic problem traumatic contact events encode over-reactive neural pathways through Hebb

local-aiarxiv-cs-ai

Mini-JEPA Foundation Model Fleet Enables Agentic Hydrologic Intelligence

arXiv:2605.14120v1 Announce Type: cross Abstract: Geospatial foundation models compress multispectral observations into dense embeddings increasingly used in natural-language environmental reasoning s