All entries

Low-Rank Adaptation Redux for Large Models

model-releasesarxiv-cs-lg

arXiv:2604.21905v1 Announce Type: new Abstract: Low-rank adaptation (LoRA) has emerged as the de facto standard for parameter-efficient fine-tuning (PEFT) of foundation models, enabling the adaptation

LRDUN: A Low-Rank Deep Unfolding Network for Efficient Spectral Compressive Imaging

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

DGX agent

arXiv:2511.18513v2 Announce Type: replace Abstract: Deep unfolding networks (DUNs) have achieved remarkable success and become the mainstream paradigm for spectral compressive imaging (SCI) reconstruc

researcharxiv-cs-cv

24 Apr 2026

M-CARE: Standardized Clinical Case Reporting for AI Model Behavioral Disorders, with a 20-Case Atlas and Experimental Validation

arXiv:2604.20871v1 Announce Type: cross Abstract: We introduce M-CARE (Model Clinical Assessment and Reporting for Evaluation), a clinical case report framework for AI model behavioral disorders adapt

Machine Behavior in Relational Moral Dilemmas: Moral Rightness, Predicted Human Behavior, and Model Decisions

arXiv:2604.21871v1 Announce Type: new Abstract: Human moral judgment is context-dependent and modulated by interpersonal relationships. As large language models (LLMs) increasingly function as decisio

safetyarxiv-cs-cl

Machine learning and digital pragmatics: Which word category influences emoji use most?

arXiv:2604.21108v1 Announce Type: new Abstract: This study investigates Machine Learning (ML) in the prediction of emojis in Arabic tweets employing the (state-of-the-art) MARBERT model. A corpus of 1

Applications

Mapping the Political Discourse in the Brazilian Chamber of Deputies: A Multi-Faceted Computational Approach

arXiv:2604.21897v1 Announce Type: new Abstract: Analyses of legislative behavior often rely on voting records, overlooking the rich semantic and rhetorical content of political speech. In this paper,

applicationsarxiv-cs-cl

MaskDiME: Adaptive Masked Diffusion for Precise and Efficient Visual Counterfactual Explanations

model-releasesarxiv-cs-cv

arXiv:2602.18792v3 Announce Type: replace Abstract: Visual counterfactual explanations aim to reveal the minimal semantic modifications that can alter a model's prediction, providing causal and interp

Materialistic RIR: Material Conditioned Realistic RIR Generation

arXiv:2604.21119v1 Announce Type: cross Abstract: Rings like gold, thuds like wood! The sound we hear in a scene is shaped not only by the spatial layout of the environment but also by the materials o

MathDuels: Evaluating LLMs as Problem Posers and Solvers

model-releasesarxiv-cs-cl

arXiv:2604.21916v1 Announce Type: new Abstract: As frontier language models attain near-ceiling performance on static mathematical benchmarks, existing evaluations are increasingly unable to different

MATRAG: Multi-Agent Transparent Retrieval-Augmented Generation for Explainable Recommendations

arXiv:2604.20848v1 Announce Type: cross Abstract: Large Language Model (LLM)-based recommendation systems have demonstrated remarkable capabilities in understanding user preferences and generating per

MCAP: Deployment-Time Layer Profiling for Memory-Constrained LLM Inference

model-releasesarxiv-cs-lg

arXiv:2604.21026v1 Announce Type: new Abstract: Deploying large language models to heterogeneous hardware is often constrained by memory, not compute. We introduce MCAP (Monte Carlo Activation Profili

mcdok at SemEval-2026 Task 13: Finetuning LLMs for Detection of Machine-Generated Code

arXiv:2604.21365v1 Announce Type: cross Abstract: Multi-domain detection of the machine-generated code snippets in various programming languages is a challenging task. SemEval-2026 Task~13 copes with

Local Ai

Measure Twice, Click Once: Co-evolving Proposer and Visual Critic via Reinforcement Learning for GUI Grounding

arXiv:2604.21268v1 Announce Type: cross Abstract: Graphical User Interface (GUI) grounding requires mapping natural language instructions to precise pixel coordinates. However, due to visually homogen

local-aiarxiv-cs-ai

Measuring and Exploiting Contextual Bias in LLM-Assisted Security Code Review

arXiv:2603.18740v2 Announce Type: replace-cross Abstract: Automated Code Review (ACR) systems integrating Large Language Models (LLMs) are increasingly adopted in software development workflows, rangi

Measuring Opinion Bias and Sycophancy via LLM-based Coercion

model-releasesarxiv-cs-cl

arXiv:2604.21564v1 Announce Type: new Abstract: Large language models increasingly shape the information people consume: they are embedded in search, consulted for professional advice, deployed as age

mGRADE: Minimal Recurrent Gating Meets Delay Convolutions for Lightweight Sequence Modeling

arXiv:2507.01829v2 Announce Type: replace-cross Abstract: Multi-timescale sequence modeling relies on capturing both local fast dynamics and global slow context; yet, maintaining these capabilities un

Micro-DualNet: Dual-Path Spatio-Temporal Network for Micro-Action Recognition

arXiv:2604.21011v1 Announce Type: new Abstract: Micro-actions are subtle, localized movements lasting 1-3 seconds such as scratching one's head or tapping fingers. Such subtle actions are essential fo

researcharxiv-cs-cv

MiMIC: Mitigating Visual Modality Collapse in Universal Multimodal Retrieval While Avoiding Semantic Misalignment

arXiv:2604.21326v1 Announce Type: cross Abstract: Universal Multimodal Retrieval (UMR) aims to map different modalities (e.g., visual and textual) into a shared embedding space for multi-modal retriev

Local Ai

Mind the Gap: Optimal and Equitable Encouragement Policies

arXiv:2309.07176v5 Announce Type: replace Abstract: In consequential domains, it is often impossible to compel individuals to take treatment, so that optimal policy rules are merely suggestions in the

local-aiarxiv-cs-lg

Mind the Prompt: Self-adaptive Generation of Task Plan Explanations via LLMs

arXiv:2604.21092v1 Announce Type: new Abstract: Integrating Large Language Models (LLMs) into complex software systems enables the generation of human-understandable explanations of opaque AI processe

Misinformation Span Detection in Videos via Audio Transcripts

arXiv:2604.21767v1 Announce Type: new Abstract: Online misinformation is one of the most challenging issues lately, yielding severe consequences, including political polarization, attacks on democracy

MISTY: High-Throughput Motion Planning via Mixer-based Single-step Drifting

arXiv:2604.21489v1 Announce Type: cross Abstract: Multi-modal trajectory generation is essential for safe autonomous driving, yet existing diffusion-based planners suffer from high inference latency d

Mitigating Lost in Multi-turn Conversation via Curriculum RL with Verifiable Accuracy and Abstention Rewards

arXiv:2510.18731v2 Announce Type: replace-cross Abstract: Large Language Models demonstrate strong capabilities in single-turn instruction following but suffer from Lost-in-Conversation (LiC), a degra

Tutorials

Mixture of Sequence: Theme-Aware Mixture-of-Experts for Long-Sequence Recommendation

arXiv:2604.20858v1 Announce Type: cross Abstract: Sequential recommendation has rapidly advanced in click-through rate prediction due to its ability to model dynamic user interests. A key challenge, h

tutorialsarxiv-cs-ai

MKJ at SemEval-2026 Task 9: A Comparative Study of Generalist, Specialist, and Ensemble Strategies for Multilingual Polarization

arXiv:2604.21370v1 Announce Type: new Abstract: We present a systematic study of multilingual polarization detection across 22 languages for SemEval-2026 Task 9 (Subtask 1), contrasting multilingual g

Modulating Cross-Modal Convergence with Single-Stimulus, Intra-Modal Dispersion

arXiv:2604.21836v1 Announce Type: cross Abstract: Neural networks exhibit a remarkable degree of representational convergence across diverse architectures, training objectives, and even data modalitie

Agents

Multi-Agent Empowerment and Emergence of Complex Behavior in Groups

arXiv:2604.21155v1 Announce Type: new Abstract: Intrinsic motivations are receiving increasing attention, i.e. behavioral incentives that are not engineered, but emerge from the interaction of an agen

agentsarxiv-cs-ai

Multilingual and Domain-Agnostic Tip-of-the-Tongue Query Generation for Simulated Evaluation

model-releasesarxiv-cs-cl

arXiv:2604.21096v1 Announce Type: cross Abstract: Tip-of-the-Tongue (ToT) retrieval benchmarks have largely focused on English, limiting their applicability to multilingual information access. In this

Multilinguality at the Edge: Developing Language Models for the Global South

arXiv:2604.21637v1 Announce Type: new Abstract: Where and how language models (LMs) are deployed determines who can benefit from them. However, there are several challenges that prevent effective depl

Agents

Multimodal Bayesian Network for Robust Assessment of Casualties in Autonomous Triage

arXiv:2512.18908v2 Announce Type: replace Abstract: Mass Casualty Incidents can overwhelm emergency medical systems and resulting delays or errors in the assessment of casualties can lead to preventab

agentsarxiv-cs-ai

Multimodal Protein Language Models for Enzyme Kinetic Parameters: From Substrate Recognition to Conformational Adaptation

arXiv:2603.12845v2 Announce Type: replace Abstract: Predicting enzyme kinetic parameters quantifies how efficiently an enzyme catalyzes a specific substrate under defined biochemical conditions. Canon

safetyarxiv-cs-cv

Multiscale Super Resolution without Image Priors

arXiv:2604.21810v1 Announce Type: new Abstract: We address the ambiguities in the super-resolution problem under translation. We demonstrate that combinations of low-resolution images at different sca

researcharxiv-cs-cv

Musical Score Understanding Benchmark: Evaluating Large Language Models' Comprehension of Complete Musical Scores

arXiv:2511.20697v4 Announce Type: replace-cross Abstract: Understanding complete musical scores entails integrated reasoning over pitch, rhythm, harmony, and large-scale structure, yet the ability of

Navigating the Clutter: Waypoint-Based Bi-Level Planning for Multi-Robot Systems

arXiv:2604.21138v1 Announce Type: cross Abstract: Multi-robot control in cluttered environments is a challenging problem that involves complex physical constraints, including robot-robot collisions, r

Nemobot Games: Crafting Strategic AI Gaming Agents for Interactive Learning with Large Language Models

arXiv:2604.21896v1 Announce Type: new Abstract: This paper introduces a new paradigm for AI game programming, leveraging large language models (LLMs) to extend and operationalize Claude Shannon's taxo

Neural surrogates for crystal growth dynamics with variable supersaturation: explicit vs. implicit conditioning

model-releasesarxiv-cs-lg

arXiv:2604.21753v1 Announce Type: cross Abstract: Simulations of crystal growth are performed by using Convolutional Recurrent Neural Network surrogate models, trained on a dataset of time sequences c

Neuro-Symbolic Manipulation Understanding with Enriched Semantic Event Chains

arXiv:2604.21053v1 Announce Type: cross Abstract: Robotic systems operating in human environments must reason about how object interactions evolve over time, which actions are currently being performe

researcharxiv-cs-cv

Local Ai

Neutron and X-ray Diffraction Reveal the Limits of Long-Range Machine Learning Potentials for Medium-Range Order in Silica Glass

arXiv:2604.21222v1 Announce Type: cross Abstract: Glassy silica is a foundational material in optics and electronics, yet accurately predicting its medium-range order (MRO) remains a major challenge f

local-aiarxiv-cs-lg

Applications

Nonlinear Causal Discovery through a Sequential Edge Orientation Approach

arXiv:2506.05590v3 Announce Type: replace-cross Abstract: Recent advances have established the identifiability of a directed acyclic graph (DAG) under additive noise models (ANMs), spurring the develo

applicationsarxiv-cs-lg

Not-a-Bandit: Provably No-Regret Drafter Selection in Speculative Decoding for LLMs

arXiv:2510.20064v2 Announce Type: replace Abstract: Speculative decoding is widely used in accelerating large language model (LLM) inference. In this work, we focus on the online draft model selection

researcharxiv-cs-lg

NPU Design for Diffusion Language Model Inference

arXiv:2601.20706v2 Announce Type: replace-cross Abstract: Diffusion-based LLMs (dLLMs) fundamentally depart from traditional autoregressive (AR) LLM inference: they leverage bidirectional attention, b

Omission Constraints Decay While Commission Constraints Persist in Long-Context LLM Agents

arXiv:2604.20911v1 Announce Type: cross Abstract: LLM agents deployed in production operate under operator-defined behavioral policies (system-prompt instructions such as prohibitions on credential di

OmniFit: Multi-modal 3D Body Fitting via Scale-agnostic Dense Landmark Prediction

model-releasesarxiv-cs-cv

arXiv:2604.21575v1 Announce Type: new Abstract: Fitting an underlying body model to 3D clothed human assets has been extensively studied, yet most approaches focus on either single-modal inputs such a

Applications

On Reasoning Behind Next Occupation Recommendation

arXiv:2604.21204v1 Announce Type: cross Abstract: In this work, we develop a novel reasoning approach to enhance the performance of large language models (LLMs) in future occupation prediction. In thi

applicationsarxiv-cs-ai

On the algebra of Koopman eigenfunctions and on some of their infinities

arXiv:2604.21825v1 Announce Type: cross Abstract: For continuous-time dynamical systems with reversible trajectories, the nowhere-vanishing eigenfunctions of the Koopman operator of the system form a

researcharxiv-cs-lg

On the Relationship between Bayesian Networks and Probabilistic Structural Causal Models

arXiv:2603.27406v2 Announce Type: replace Abstract: In this paper, the relationship between probabilistic graphical models, in particular Bayesian networks, and causal diagrams, also called structural

On the Role of Preprocessing and Memristor Dynamics in Reservoir Computing for Image Classification

arXiv:2604.21602v1 Announce Type: cross Abstract: Reservoir computing (RC) is an emerging recurrent neural network architecture that has attracted growing attention for its low training cost and modes

Open-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics

arXiv:2604.21017v1 Announce Type: cross Abstract: Autonomous medical robots hold promise to improve patient outcomes, reduce provider workload, democratize access to care, and enable superhuman precis