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arXiv:2605.09764v1 Announce Type: cross Abstract: LLM-guided evolutionary methods such as AlphaEvolve have proven effective in domains like math, systems research, and algorithmic discovery, but their

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Research

LLM-FE: Automated Feature Engineering for Tabular Data with LLMs as Evolutionary Optimizers

DGX agent

arXiv:2503.14434v3 Announce Type: replace-cross Abstract: Automated feature engineering plays a critical role in improving predictive model performance for tabular learning tasks. Traditional automate

researcharxiv-cs-ai

12 May 2026

Local LMO: Constrained Gradient Optimization via a Local Linear Minimization Oracle

arXiv:2605.08850v1 Announce Type: cross Abstract: We design Local LMO - a new projection-free gradient-type method for constrained optimization. The key algorithmic idea is to replace the global linea

Loom: Hybrid Retrieval-Scoring Outfit Recommendation with Semantic Material Compatibility and Occasion-Aware Embedding Priors

arXiv:2605.09830v1 Announce Type: cross Abstract: We present Loom, an outfit recommendation system that combines neural embedding retrieval with structured domain scoring to generate complete, coheren

Lost in Translation? Exploring the Shift in Grammatical Gender from Latin to Occitan

arXiv:2605.09156v1 Announce Type: cross Abstract: The diachronic evolution from Latin to the Romance languages involved a restructuring of the grammatical gender system from a tripartite configuration

Low-Cost Neural Radiance Fields

arXiv:2605.09312v1 Announce Type: new Abstract: Neural Radiance Fields (NeRF) achieve high-quality novel-view synthesis, but their long training times and reliance on dense input views limit accessibi

LPT: Less-overfitting Prompt Tuning for Vision-Language Model

arXiv:2410.10247v3 Announce Type: replace-cross Abstract: Vision-language models (VLMs) have demonstrated exceptional generalization capabilities for downstream tasks. Due to its efficiency, prompt le

Machine Learning-Based Graph Simplification for Symbolic Accelerators

arXiv:2605.08996v1 Announce Type: new Abstract: Graph-based accelerators have been widely adopted in symbolic data processing applications such as genomics, cybersecurity, and artificial intelligence.

Majority Bit-Aware Watermarking For Large Language Models

arXiv:2508.03829v2 Announce Type: replace Abstract: The growing deployment of Large Language Models (LLMs) has raised concerns about their misuse in generating harmful or deceptive content. To address

Many Needles in a Haystack: Active Hit Discovery for Perturbation Experiments

arXiv:2605.10196v1 Announce Type: new Abstract: High-throughput gene perturbation experiments can test several genetic interventions in parallel, yet experimental budgets remain limited. A central goa

Tutorials

Markerless Head Tracking for Accurate and Accessible Neuronavigation

arXiv:2602.07052v2 Announce Type: replace Abstract: Neuronavigation is widely used in biomedical research and interventions to guide the precise placement of instruments around the head to support pro

tutorialsarxiv-cs-cv

Masked Generative Transformer Is What You Need for Image Editing

arXiv:2605.10859v1 Announce Type: new Abstract: Diffusion models dominate image editing, yet their global denoising mechanism entangles edited regions with surrounding context, causing modifications t

Matching Meaning at Scale: Evaluating Semantic Search for 18th-Century Intellectual History through the Case of Locke

arXiv:2605.09236v1 Announce Type: cross Abstract: While digitized corpora have transformed the study of intellectual transmission, current methods rely heavily on lexical text reuse detection, capturi

Matrix Factorization for Practical Continual Mean Estimation Under User-Level Differential Privacy

arXiv:2601.22320v2 Announce Type: replace Abstract: We study continual mean estimation, where data vectors arrive sequentially and the goal is to maintain accurate estimates of the running mean. We ad

Max-pooling Network Revisited: Analyzing the Role of Semantic Probability in Multiple Instance Learning for Hallucination Detection

arXiv:2605.08863v1 Announce Type: new Abstract: Hallucination detection has become increasingly important for improving the reliability of large language models (LLMs). Recently, hybrid approaches suc

Measurement-Adapted Eigentask Representations for Photon-Limited Optical Readout

arXiv:2605.10008v1 Announce Type: cross Abstract: Optical readout in low-light imaging is fundamentally limited by measurement noise, including photon shot noise, detector noise, and quantization erro

Measuring and Decomposing Mode Separation via the Canonical Diffusion

arXiv:2605.08777v1 Announce Type: cross Abstract: Mode separation, namely how sharply a distribution fragments into barrier-separated clusters, is a fundamental geometric property of densities, diffic

Measuring Embedding Sensitivity to Authorial Style in French: Comparing Literary Texts with Language Model Rewritings

arXiv:2605.10606v1 Announce Type: cross Abstract: Large language models (LLMs) can convincingly imitate human writing styles, yet it remains unclear how much stylistic information is encoded in embedd

Mechanistic Independence: A Principle for Identifiable Disentangled Representations

arXiv:2509.22196v2 Announce Type: replace Abstract: Disentangled representations seek to recover latent factors of variation underlying observed data, yet their identifiability is still not fully unde

MedThink: Enhancing Diagnostic Accuracy in Small Models via Teacher-Guided Reasoning Correction

arXiv:2605.08094v1 Announce Type: cross Abstract: Accurate clinical diagnosis requires extensive domain knowledge and complex clinical reasoning capabilities. Although large language models (LLMs) hol

Mela: Test-Time Memory Consolidation based on Transformation Hypothesis

arXiv:2605.10537v1 Announce Type: new Abstract: Memory consolidation, the process by which transient experiences are transformed into stable, structured representations, is a foundational organizing p

Memorize Theorems, Not Instances: Probing SFT Generalization through Mathematical Reasoning

arXiv:2605.09270v1 Announce Type: cross Abstract: Supervised Fine-Tuning (SFT) is widely used for task-specific adaptation, yet recent work shows it systematically undermines reasoning generalization.

MeshFIM: Local Low-Poly Mesh Editing via Fill-in-the-Middle Autoregressive Generation

arXiv:2605.08744v1 Announce Type: cross Abstract: Autoregressive (AR) models can generate high-quality low-poly meshes from point clouds, but they still operate in an all-or-nothing manner: when a loc

Metacognitive Behavioral Tuning of Large Language Models for Multi-Hop Question Answering

arXiv:2602.22508v2 Announce Type: replace Abstract: Large Language Models (LLMs) often produce incorrect answers on multi-hop question answering even when the reasoning trace already contains a correc

METBRA25Y: Brazil Surface Meteorology Archive with Harmonized Variables and Quality Control

arXiv:2605.08701v1 Announce Type: new Abstract: This data paper describes METBRA25Y, a harmonized archive of hourly surface meteorological observations from Brazil derived from public historical recor

Micro-Defects Expose Macro-Fakes: Detecting AI-Generated Images via Local Distributional Shifts

arXiv:2605.09296v1 Announce Type: cross Abstract: Recent generative models can produce images that appear highly realistic, raising challenges in distinguishing real and AI-generated images. Yet exist

MicroDiffuse3D: A Foundation Model for 3D Microscopy Imaging Restoration

arXiv:2605.08566v1 Announce Type: new Abstract: Chemical imaging enables label-free visualization of cells, tissues and living systems while providing direct biochemical information that is difficult

MicroViTv2: Beyond the FLOPS for Edge Energy-Friendly Vision Transformers

arXiv:2605.10148v1 Announce Type: new Abstract: The Vision Transformer (ViT) achieves remarkable accuracy across visual tasks but remains computationally expensive for edge deployment. This paper pres

Mind the Gap No More: Achieving Zero-Gap Multimodal Integration via One Tokenizer

arXiv:2602.12286v2 Announce Type: replace-cross Abstract: A central challenge in developing Multimodal Large Language Models (MLLMs) is effectively integrating heterogeneous inputs into a cohesive rea

MineEvolve: Self-Evolution with Accumulated Knowledge for Long-Horizon Embodied Minecraft Agents

arXiv:2603.13131v3 Announce Type: replace Abstract: Long-horizon embodied intelligence requires agents to improve through interaction, not merely to execute plans generated from static goals. A centra

Minimal Filling Architectures of Polynomial Neural Networks: Counterexamples, Frontier Search, and Defects

arXiv:2605.09609v1 Announce Type: new Abstract: We provide a counterexample to the minimal unimodal conjecture for polynomial neural networks (PNNs) with power activation functions. Fixing the input a

Mistake-Bounded Language Generation

arXiv:2605.10809v1 Announce Type: new Abstract: We investigate the learning task of language generation in the limit, but shift focus from the traditional time-of-last-mistake metric of a generator's

Mitigating Membership Inference in Intermediate Representations with Differentially Private Training

arXiv:2602.22611v2 Announce Type: replace Abstract: In Embedding-as-an-Interface (EaaI) settings, pre-trained models are queried for Intermediate Representations (IRs). The distributional properties o

Mitigating Watermark Forgery in Generative Models via Randomized Key Selection

arXiv:2507.07871v4 Announce Type: replace-cross Abstract: Watermarking enables GenAI providers to verify whether content was generated by their models. A watermark is a hidden signal in the content, w

Mixture of Experts for Recognizing Depression from Interview and Reading Tasks

arXiv:2502.20213v2 Announce Type: replace Abstract: Depression is a mental disorder and can cause a variety of symptoms, including psychological, physical, and social. Speech has been proved an object

Mixture of Layers with Hybrid Attention

arXiv:2605.09516v1 Announce Type: cross Abstract: Standard Mixture-of-Experts (MoE) transformers route tokens to expert subnetworks within each layer, but the layer structure itself remains monolithic

ML-CLIPSim: Multi-Layer CLIP Similarity for Machine-Oriented Image Quality

arXiv:2605.09479v1 Announce Type: cross Abstract: We study full-reference image quality assessment from a machine-centric perspective, where images are evaluated by how well they preserve information

MOBIUS: A Multi-Modal Bipedal Robot that can Walk, Crawl, Climb, and Roll

arXiv:2511.01774v3 Announce Type: replace Abstract: This paper presents the MOBIUS platform, a bipedal robot capable of walking, crawling, climbing, and rolling. MOBIUS features four limbs, two 6-DoF

researcharxiv-cs-ro

Model-based Dynamic 3D MRI Reconstructions using Neural Fields and Tensor Product Expansions

arXiv:2605.08275v1 Announce Type: cross Abstract: Conventional MRI reconstruction methods treat images and coil sensitivities as discrete objects, leading to high memory demands and limited structural

Model Merging Scaling Laws in Large Language Models

arXiv:2509.24244v4 Announce Type: replace Abstract: We study empirical scaling laws for language model merging measured by cross-entropy. Despite its wide practical use, merging lacks a quantitative r

Model-Reference Adaptive Flight Control of the 95-mg Bee++

arXiv:2605.08525v1 Announce Type: new Abstract: We introduce a model-reference adaptive control (MRAC) architecture for high-performance positional tracking of the Bee++, a 95-mg insect-scale flapping

researcharxiv-cs-ro

Modeling Atomic Conformational Ensembles of Proteins via Test-Time Supervision of Boltz-2 on Cryo-EM Density Maps

arXiv:2605.09832v1 Announce Type: new Abstract: Knowledge of a protein's atomic conformational ensemble is critical to determining its function, yet state-of-the-art ensemble prediction models are lim

MoPO: Incorporating Motion Prior for Occluded Human Mesh Recovery

arXiv:2605.09856v1 Announce Type: cross Abstract: Although recent studies have made remarkable progress in human mesh recovery, they still exhibit limited robustness to occlusions and often produce in

Multi-Armed Bandits With Best-Action Queries

arXiv:2605.08287v1 Announce Type: cross Abstract: We study multi-armed bandits (MABs) augmented with best-action queries, in which the learner may additionally query an oracle that reveals the best ar

MultiAnimate: Pose-Guided Image Animation Made Extensible

arXiv:2602.21581v2 Announce Type: replace Abstract: Pose-guided human image animation aims to synthesize realistic videos of a reference character driven by a sequence of poses. While diffusion-based

Multifidelity Gaussian process regression for solving nonlinear partial differential equations

arXiv:2605.10383v1 Announce Type: cross Abstract: Solving nonlinear partial differential equations (PDEs) using kernel methods offers a compelling alternative to traditional numerical solvers. However

MultiMedVision: Multi-Modal Medical Vision Framework

arXiv:2605.09151v1 Announce Type: new Abstract: Multi-modal medical imaging enables comprehensive diagnostics, yet current foundation models process 2D (e.g. X-ray) and 3D (e.g. CT) data with separate

Multimodal Emotion Recognition via Causal-Diffusion Bridge (Affect-Diff)

arXiv:2605.08252v1 Announce Type: new Abstract: Multimodal emotion recognition on CMU-MOSEI faces an extreme imbalance as Happy accounts for 65.9% of samples while three Ekman categories collectively