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Localising Dropout Variance in Twin Networks

arXiv:2507.03622v2 Announce Type: replace Abstract: Accurate individual treatment-effect estimation demands not only reliable point predictions but also uncertainty measures that help practitioners lo

Local Ai

Localization Boosting for Growth Markets: Mitigating Cross-Locale Behavioral Bias in Learning-to-Rank

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DGX agent

arXiv:2605.11272v1 Announce Type: new Abstract: Adobe Express is expanding internationally, but the US has a disproportionately large content supply and interaction volume. Learning-to-rank (LTR) mode

local-aiarxiv-cs-lg

13 May 2026

LOFT: Low-Rank Orthogonal Fine-Tuning via Task-Aware Support Selection

model-releasesarxiv-cs-lg

arXiv:2605.11872v1 Announce Type: new Abstract: Orthogonal parameter-efficient fine-tuning (PEFT) adapts pretrained weights through structure-preserving multiplicative transformations, but existing me

Logit-Attention Divergence: Mitigating Position Bias in Multi-Image Retrieval via Attention-Guided Calibration

arXiv:2605.11591v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have shown strong performance in multi-image cross-modal retrieval, yet suffer from severe position bias, where

Long Story Short: Disentangling Compositionality and Long-Caption Understanding in Contrastive VLMs

model-releasesarxiv-cs-cv

arXiv:2509.19207v2 Announce Type: replace Abstract: Contrastive vision-language models (VLMs) have made significant progress in binding visual and textual information, yet understanding long, composit

LongMemEval-V2: Evaluating Long-Term Agent Memory Toward Experienced Colleagues

arXiv:2605.12493v1 Announce Type: new Abstract: Long-term memory is crucial for agents in specialized web environments, where success depends on recalling interface affordances, state dynamics, workfl

Looking and Listening Inside and Outside: Multimodal Artificial Intelligence Systems for Driver Safety Assessment and Intelligent Vehicle Decision-Making

arXiv:2602.07668v2 Announce Type: replace Abstract: The looking-in-looking-out (LILO) framework has enabled intelligent vehicle applications that understand both the outside scene and the driver state

LoopUS: Recasting Pretrained LLMs into Looped Latent Refinement Models

arXiv:2605.11011v1 Announce Type: new Abstract: Looped computation shows promise in improving the reasoning-oriented performance of LLMs by scaling test-time compute. However, existing approaches typi

Lower bounds for one-layer transformers that compute parity

arXiv:2605.12171v1 Announce Type: new Abstract: This note shows that no self-attention layer post-processed by a rational function can sign-represent the parity function unless the product of the numb

Local Ai

LPDP: Inference-Time Reward Control for Variable-Length DNA Generation with Edit Flows

arXiv:2605.11368v1 Announce Type: new Abstract: We study the application of recent Edit Flows for inference-time reward control for DNA sequence generation. Unlike most reward-guided DNA generation fr

local-aiarxiv-cs-lg

LucidFlux: Caption-Free Photo-Realistic Image Restoration via a Large-Scale Diffusion Transformer

arXiv:2509.22414v4 Announce Type: replace Abstract: Image restoration (IR) aims to recover images degraded by unknown mixtures while preserving semanticsconditions under which discriminative restorers

LucidNFT: LR-Anchored Multi-Reward Preference Optimization for Flow-Based Real-World Super-Resolution

arXiv:2603.05947v3 Announce Type: replace Abstract: Generative real-world image super-resolution (Real-ISR) can synthesize visually convincing details from severely degraded low-resolution (LR) inputs

Agents

LychSim: A Controllable and Interactive Simulation Framework for Vision Research

arXiv:2605.12449v1 Announce Type: new Abstract: While self-supervised pretraining has reduced vision systems' reliance on synthetic data, simulation remains an indispensable tool for closed-loop optim

agentsarxiv-cs-cv

M^4-SAM: Multi-Modal Mixture-of-Experts with Memory-Augmented SAM for RGB-D Video Salient Object Detection

arXiv:2605.11760v1 Announce Type: new Abstract: The Segment Anything Model 2 (SAM2) has emerged as a foundation model for universal segmentation. Owing to its generalizable visual representations, SAM

applicationsarxiv-cs-cv

Agents

MAC: Masked Agent Collaboration Boosts Large Language Model Medical Decision-Making

arXiv:2507.21159v3 Announce Type: replace-cross Abstract: Large language models (LLMs) have proven effective in artificial intelligence, where the multi-agent system (MAS) holds considerable promise f

agentsarxiv-cs-lg

Machine Learning for neutron source distributions

arXiv:2605.12165v1 Announce Type: cross Abstract: In light of the recent advancements in machine learning, we propose a novel approach to neutron source distribution estimation through the utilisation

MajinBook: An open catalogue of digitally mediated world literature

arXiv:2511.11412v5 Announce Type: replace Abstract: This data paper introduces MajinBook, an open catalogue designed to facilitate the use of shadow libraries-such as Library Genesis and Z-Library-for

safetyarxiv-cs-cl

Make It Long, Keep It Fast: End-to-End 10k-Sequence Modeling at Billion Scale on Douyin Recommendation

arXiv:2511.06077v2 Announce Type: replace Abstract: Short-video recommenders such as Douyin must exploit extremely long user histories without breaking latency or cost budgets. We present an end-to-en

MambaNetBurst: Direct Byte-level Network Traffic Classification without Tokenization or Pretraining

arXiv:2605.11034v1 Announce Type: cross Abstract: We present MambaNetBurst, a compact tokenizer-free byte-level sequence classifier for network burst classification based on a Mamba-2 backbone. In con

Manifold Sampling via Entropy Maximization

arXiv:2605.12338v1 Announce Type: new Abstract: Sampling from constrained distributions has a wide range of applications, including in Bayesian optimization and robotics. Prior work establishes conver

Mapping Embodied Affective Touch Strategies on a Humanoid Robot

arXiv:2605.11825v1 Announce Type: new Abstract: Affective touch in human-robot interaction is shaped not only by emotional intent, but also by robot embodiment, including touch location, physical cons

researcharxiv-cs-ro

Martingale-Consistent Self-Supervised Learning

arXiv:2605.11846v1 Announce Type: new Abstract: Self-supervised learning (SSL) is often deployed under changing information, such as shorter histories, missing features, or partially observed images.

MaskTab: Scalable Masked Tabular Pretraining with Scaling Laws and Distillation for Industrial Classification

arXiv:2605.11408v1 Announce Type: cross Abstract: Tabular data forms the backbone of high-stakes decision systems in finance, healthcare, and beyond. Yet industrial tabular datasets are inherently dif

applicationsarxiv-cs-cl

Maximin Robust Bayesian Experimental Design

arXiv:2603.14094v2 Announce Type: replace-cross Abstract: We address the brittleness of Bayesian experimental design under model misspecification by formulating the problem as a max--min game between

safetyarxiv-cs-lg

Agents

MCPShield: Content-Aware Attack Detection for LLM Agent Tool-Call Traffic

arXiv:2605.11053v1 Announce Type: cross Abstract: The Model Context Protocol (MCP) has become a widely adopted interface for LLM agents to invoke external tools, yet learned monitoring of MCP tool-cal

agentsarxiv-cs-lg

Measuring Accuracy and Energy-to-Solution of Quantum Fine-Tuning of Foundational AI Models

arXiv:2605.02798v1 Announce Type: cross Abstract: We present an experimental study of energy-to-solution (ETS) of hybrid quantum-classical applications, enabled by direct instrumentation of power cons

Measuring Five-Nines Reliability: Sample-Efficient LLM Evaluation in Saturated Benchmarks

model-releasesarxiv-cs-lg

arXiv:2605.11209v1 Announce Type: new Abstract: While existing benchmarks demonstrate the near-perfect performance of large language models (LLMs) on various tasks, this apparent saturation often obsc

Mechanistic Interpretability of ASR models using Sparse Autoencoders

arXiv:2605.12225v1 Announce Type: new Abstract: Understanding the internal machinations of deep Transformer-based NLP models is more crucial than ever as these models see widespread use in various dom

applicationsarxiv-cs-cl

MedHopQA: A Disease-Centered Multi-Hop Reasoning Benchmark and Evaluation Framework for LLM-Based Biomedical Question Answering

arXiv:2605.12361v1 Announce Type: new Abstract: Evaluating large language models (LLMs) in the biomedical domain requires benchmarks that can distinguish reasoning from pattern matching and remain dis

MEME: Multi-entity & Evolving Memory Evaluation

arXiv:2605.12477v1 Announce Type: cross Abstract: LLM-based agents increasingly operate in persistent environments where they must store, update, and reason over information across many sessions. Whil

MetaColloc: Optimization-Free PDE Solving via Meta-Learned Basis Functions

arXiv:2605.12368v1 Announce Type: new Abstract: Solving partial differential equations (PDEs) with machine learning typically requires training a new neural network for every new equation. This optimi

Metaphor Is Not All Attention Needs

arXiv:2605.12128v1 Announce Type: new Abstract: Large language models are increasingly deployed in safety-critical applications, where their ability to resist harmful instructions is essential. Althou

safetyarxiv-cs-cl

MieDB-100k: A Comprehensive Dataset for Medical Image Editing

arXiv:2602.09587v2 Announce Type: replace Abstract: The scarcity of high-quality data remains a primary bottleneck in adapting multimodal generative models for medical image editing. Existing medical

researcharxiv-cs-cv

Tutorials

Mind the Pause: Disfluency-Aware Objective Tuning for Multilingual Speech Correction with LLMs

arXiv:2605.12242v1 Announce Type: new Abstract: Automatic Speech Recognition (ASR) transcripts often contain disfluencies, such as fillers, repetitions, and false starts, which reduce readability and

tutorialsarxiv-cs-cl

Minimax Rates and Spectral Distillation for Tree Ensembles

arXiv:2605.11841v1 Announce Type: cross Abstract: Tree ensembles such as random forests (RFs) and gradient boosting machines (GBMs) are among the most widely used supervised learners, yet their theore

Missing Old Logits in Asynchronous Agentic RL: Semantic Mismatch and Repair Methods for Off-Policy Correction

arXiv:2605.12070v1 Announce Type: new Abstract: Asynchronous reinforcement learning improves rollout throughput for large language model agents by decoupling sample generation from policy optimization

safetyarxiv-cs-lg

Missingness-MDPs: Bridging the Theory of Missing Data and POMDPs

arXiv:2605.12262v1 Announce Type: cross Abstract: We introduce missingness-MDPs (miss-MDPs), a novel subclass of partially observable Markov decision processes (POMDPs) that incorporates the theory of

MIST: Reliable Streaming Decision Trees for Online Class-Incremental Learning via McDiarmid Bound

arXiv:2605.11617v1 Announce Type: new Abstract: Streaming decision trees are natural candidates for open-world continual learning, as they perform local updates, enjoy bounded memory, and static decis

Local Ai

Mitigating Action-Relation Hallucinations in LVLMs via Relation-aware Visual Enhancement

arXiv:2605.11808v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) have achieved remarkable performance on diverse vision-language tasks. However, LVLMs still suffer from hallucinati

local-aiarxiv-cs-cv

Mitigating Context-Memory Conflicts in LLMs through Dynamic Cognitive Reconciliation Decoding

arXiv:2605.12185v1 Announce Type: new Abstract: Large language models accumulate extensive parametric knowledge through pre-training. However, knowledge conflicts occur when outdated or incorrect para

Hardware

MLCommons Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces

arXiv:2605.11333v1 Announce Type: cross Abstract: The fast pace of artificial intelligence~(AI) innovation demands an agile methodology for observation, reproduction and optimization of distributed ma

hardwarearxiv-cs-lg

Mobile Traffic Camera Calibration from Road Geometry for UAV-Based Traffic Surveillance

arXiv:2605.11900v1 Announce Type: new Abstract: Unmanned aerial vehicles (UAVs) can provide flexible traffic surveillance where fixed roadside cameras are unavailable, costly, or impractical. However,

researcharxiv-cs-cv

MobileEgo Anywhere: Open Infrastructure for long horizon egocentric data on commodity hardware

arXiv:2605.05945v2 Announce Type: replace-cross Abstract: The recent advancement of Vision Language Action (VLA) models has driven a critical demand for large scale egocentric datasets. However, exist

researcharxiv-cs-cl

MoCam: Unified Novel View Synthesis via Structured Denoising Dynamics

arXiv:2605.12119v1 Announce Type: new Abstract: Generative novel view synthesis faces a fundamental dilemma: geometric priors provide spatial alignment but become sparse and inaccurate under view chan

Modality-Inconsistent Continual Learning of Multimodal Large Language Models

arXiv:2412.13050v2 Announce Type: replace-cross Abstract: In this paper, we introduce Modality-Inconsistent Continual Learning (MICL), a new continual learning scenario for Multimodal Large Language M

Model-based Bootstrap of Controlled Markov Chains

arXiv:2605.12410v1 Announce Type: cross Abstract: We propose and analyze a model-based bootstrap for transition kernels in finite controlled Markov chains (CMCs) with possibly nonstationary or history

safetyarxiv-cs-lg

Model-Level GNN Explanations via Rule-to-Graph Readout for Logit Reconstruction

arXiv:2503.09051v2 Announce Type: replace Abstract: We propose a novel model-level GNN explanation framework that shifts the explanation target from class-wise rule extraction to rule-based logit reco

Modeling Narrative Structure in Latin Epic Poetry with Automatically Generated Story Grammars

arXiv:2502.12276v2 Announce Type: replace Abstract: Computational methods for analyzing prose and poetry utilize word embeddings and other abstract representations that sometimes obscure context-rich

researcharxiv-cs-cl