research

Formalization of Malagasy conjugation

arXiv:2605.27161v1 Announce Type: new Abstract: This paper reports the core linguistic work performed to construct a dictionary-based morphological analyser for Malagasy simple verbs. It uses the Unit

Frequency-Guided Fusion For RGB-Thermal Semantic Segmentation

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arXiv:2605.26273v1 Announce Type: new Abstract: Semantic segmentation in complex environments such as urban driving scenes remains challenging under adverse lighting conditions, where RGB images alone

researcharxiv-cs-cv

27 May 2026

From Contrast to Consistency: Rethinking Event-based Continuous-Time Optical Flow Estimation

arXiv:2605.25570v2 Announce Type: replace Abstract: Estimating continuous optical flow is a fundamental yet challenging problem in dynamic visual perception. Event-based cameras, with microsecond late

From Privacy to Generalization: Linear Max-Information Bounds for DP-SGD

arXiv:2605.26222v1 Announce Type: new Abstract: Understanding the relationship between generalization and privacy remains a central challenge in modern machine learning theory, particularly for deep n

From Scores to Gibbs Correctors: Accelerating Uniform-Rate Discrete Diffusion Models

arXiv:2605.27352v1 Announce Type: new Abstract: Discrete diffusion models have achieved strong empirical performance in text and other symbolic domains, but, especially for uniform-rate models, they o

From Snippets to Semantics: Rethinking Evidence Granularity for Multilingual Fact Verification

arXiv:2605.26755v1 Announce Type: new Abstract: Multilingual fact verification requires evidence that is both relevant and sufficiently complete for reliable factuality prediction. However, existing s

FUCK YEAHHHHHH ANTHROPIC IS NO LONGER DOOMING ABOUT JOBS!!!!! ♥️♥️♥️

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researchyann-lecun--x

GAC: Noise-Aware Adaptive Mixing for Hybrid SFT-RL Post-Training

arXiv:2605.26184v1 Announce Type: cross Abstract: Hybrid post-training usually combines supervised fine-tuning and reinforcement learning, but fixed mixing schedules cannot adapt when the relative noi

Garment Particles: A 2D--3D Symmetric Garment Representation for Generation and Editing

arXiv:2605.26391v1 Announce Type: cross Abstract: Practical garment design spans two modes: intuitive creation from high-level intent, such as a reference image or text description, and complex low-le

Generating realistic global precipitation fields from modelled atmospheric circulation

arXiv:2504.00307v2 Announce Type: replace Abstract: Improving the representation of precipitation in Earth system models (ESMs) is critical for assessing the impacts of climate change and especially o

Generating Robust Portfolios of Optimization Models using Large Language Models

arXiv:2605.27013v1 Announce Type: new Abstract: Mathematical optimization is a powerful tool for structured decision-making across domains such as resource allocation and planning. Formulating optimiz

Genre Controlled Music Generation via Activation Steering

arXiv:2506.10225v2 Announce Type: replace-cross Abstract: Computational Music Generation is evolving towards non-conventional styles, demanding methods that enable precise and controllable blending of

Geometrically Constrained Outlier Synthesis

arXiv:2603.08413v2 Announce Type: replace-cross Abstract: Deep neural networks for image classification often exhibit overconfidence on out-of-distribution (OOD) samples. To address this, we introduce

Geometry-Aware Contrastive Learning for Few-Shot Automatic Modulation Recognition

arXiv:2605.26600v1 Announce Type: cross Abstract: Standard Self-Supervised Learning (SSL) for Automatic Modulation Recognition (AMR) struggles with ineffective isotropic augmentations, spectral instab

Get a state of the art protein structure prediction in just 9 lines of code. No MSAs needed.

Get a state of the art protein structure prediction in just 9 lines of code. No MSAs needed. I'm so excited to show the world what we've been working on the for the past months!! I'm going to highligh

researchyann-lecun--x

Global Structure-from-Motion Meets Feedforward Reconstruction

arXiv:2605.26103v2 Announce Type: replace Abstract: Structure-from-Motion -- the process of simultaneously estimating camera poses and 3D scene structure from a collection of images -- remains a centr

Granuscore: A Reference-Free Measure of Granularity for Text Analysis and Question Answering

arXiv:2605.26620v1 Announce Type: new Abstract: Natural language conveys information at varying levels of granularity, from fine-grained references to broad descriptions. While granularity is fundamen

Graph is a Substrate Across Data Modalities

arXiv:2601.22384v2 Announce Type: replace-cross Abstract: Graphs provide a natural representation of relational structure that arises across diverse domains. Despite this ubiquity, graph structure is

GraphReview: Scientific Paper Evaluation via LLM-Based Graph Message Passing

arXiv:2605.27204v1 Announce Type: new Abstract: Scientific paper evaluation often involves not only assessing a manuscript itself, but also relating it to contemporaneous research and prior literature

Greening AI Inference with Accuracy and Latency-aware User Incentives

arXiv:2605.27309v1 Announce Type: new Abstract: The widespread use of AI services has raised concerns for its environmental sustainability, towards which recent studies have identified carbon emission

GS-CLIP: Zero-shot 3D Anomaly Detection by Geometry-Aware Prompt and Synergistic View Representation Learning

arXiv:2602.19206v3 Announce Type: replace Abstract: Zero-shot 3D Anomaly Detection is an emerging task that aims to detect anomalies in a target dataset without any target training data, which is part

GUI-Libra: Training Native GUI Agents to Reason and Act with Action-aware Supervision and Partially Verifiable RL

arXiv:2602.22190v2 Announce Type: replace-cross Abstract: Open-source native GUI agents still lag behind closed-source systems on long-horizon navigation tasks. This gap stems from two limitations: a

Guiding LLM Post-training Data Engineering with Model Internals from Sparse Autoencoders

arXiv:2605.27354v1 Announce Type: cross Abstract: Model internals encode rich information about how a large language model (LLM) processes its training data; however, post-training data engineering la

Gumbel Machine: Counterfactual Student Writing Generation via Gumbel Noise Steering

arXiv:2605.27249v1 Announce Type: new Abstract: An effective method of teaching across disciplines is to provide examples of high-quality work. However, an example may be significantly different from

High-Quality Synthetic Financial Time-Series using a GAN-Diffusion Framework

arXiv:2605.27113v1 Announce Type: cross Abstract: In recent years, financial institutions and firms have increasingly adopted synthetic data to address data scarcity and to generate counterfactual mar

HiSpec: Hierarchical Speculative Decoding for LLMs

arXiv:2510.01336v2 Announce Type: replace-cross Abstract: Speculative decoding accelerates LLM inference by using a smaller draft model to speculate tokens that a larger target model verifies. Verific

HydraPrompt: An Adaptive and Asymmetric Framework of Vision-Language Models for Synthetic Image Detection

arXiv:2605.26421v1 Announce Type: new Abstract: The rapid evolution of generative models has precipitated a proliferation of fabricated content, posing significant challenges to existing Synthetic Ima

ICICLE: Expanding Retrieval with In-Context Documents

arXiv:2605.26902v1 Announce Type: cross Abstract: Generative retrieval (GR) maps queries directly to document identifiers (docids) using parametric knowledge, However, this design makes corpus expansi

If you have been experiencing issues with OpenAI Codex oAuth, it is now fixed. OpenAI has been fixing it in the background and then seemed t…

If you have been experiencing issues with OpenAI Codex oAuth, it is now fixed. OpenAI has been fixing it in the background and then seemed to change their whole spec today to solve it, you must `herme

researchnous-research--x

Image Feature Fusion-based Federated Client Unlearning (FCU)

arXiv:2605.26715v1 Announce Type: new Abstract: Major data protection regulations all mention the 'right to be forgotten,' and that's what pushed federated unlearning (FU) techniques forward. But one

Inference-Time Search Using Side Information for Diffusion-Based Image Reconstruction

arXiv:2510.03352v3 Announce Type: replace-cross Abstract: Diffusion models have been used as priors for solving inverse problems. However, existing approaches typically overlook side information that

Inferring Group Intent as a Cooperative Game. An NLP-based Framework for Trajectory Analysis

arXiv:2510.23905v2 Announce Type: replace-cross Abstract: This paper studies group target trajectory intent as the outcome of a cooperative game where the complex-spatio trajectories are modeled using

Information Theoretic Perspective on Representation Learning

arXiv:2601.11334v2 Announce Type: replace-cross Abstract: An information-theoretic framework is introduced to analyze last-layer embedding, focusing on learned representations for regression tasks. We

Innovation: An Almost Characterization of Hallucination

arXiv:2605.26808v1 Announce Type: cross Abstract: Hallucination is a central limitation of large language models (LLMs), and substantial effort has been devoted to understanding and mitigating it. Tow

Innovative Silicosis and Pneumonia Classification: Leveraging Graph Transformer Post-hoc Modeling and Ensemble Techniques

arXiv:2501.00520v2 Announce Type: replace Abstract: This paper presents a comprehensive study on the classification and detection of Silicosis-related lung inflammation. Our main contributions include

Is an Image Also Worth 16x16=256 Superpixels? A Framework for Attentional Image Classification

arXiv:2605.27144v1 Announce Type: new Abstract: Superpixel-based image classification has traditionally leveraged graph neural networks (GNNs) for processing irregular image representations. Recent ad

ISTASTrack: Bridging ANN and SNN via ISTA Adapter for RGB-Event Tracking

arXiv:2509.09977v2 Announce Type: replace Abstract: RGB-Event tracking has become a promising trend in visual object tracking to leverage the complementary strengths of both RGB images and dynamic spi

JLT: Clean-Latent Prediction in Latent Diffusion Transformers

arXiv:2605.27102v1 Announce Type: new Abstract: Flow matching with clean-data prediction has shown that regressing the clean point can exploit low-dimensional structure more effectively than predictin

Joint Instance Segmentation and Geometric Attribute Regression for Roof Structures in Aerial Imagery

arXiv:2605.26370v1 Announce Type: new Abstract: We present a method for jointly predicting instance-level roof segment masks together with three continuous geometric attributes -- building height, roo

Kan Extension Transformers: A Categorical Unification of Attention, Diffusion, and Predict-Detach Self-Conditioning

arXiv:2605.27259v1 Announce Type: new Abstract: We propose Kan Extension Transformers (KETs) as a unifying categorical framework for a diverse group of Transformer implementations. The core claim is t

L-Learning : A Lyapunov-Based Approach Leveraging Lagrangian Mechanics for Efficient and Stable Robot Tracking

arXiv:2605.26648v1 Announce Type: new Abstract: This paper presents L-Learning, a novel data-driven control framework for robotics that integrates Lyapunov stability theory with Lagrangian mechanics t

researcharxiv-cs-ro

LATTE: Forecasting Peer Anchored Preference Trajectories for Personalized LLM Generation

arXiv:2605.26612v1 Announce Type: new Abstract: Personalized generation with frozen large language models requires a conditioning signal that is both compact and current. Existing personalization meth

Learning Nonlinear Factor Models with Unknown Monotone Links from Incomplete and Noisy Data

arXiv:2605.26271v1 Announce Type: cross Abstract: We study a nonlinear factor model in which observed responses depend on low-rank latent factors through an unknown monotone link function. This settin

Learning Reference-Guided Exposure Correction with Hybrid Illumination Characteristics

arXiv:2605.26729v1 Announce Type: new Abstract: We present HICNet, a reference-guided exposure correction framework. A lightweight, content-agnostic encoder distills each image into a compact illumina

Learning to Adapt SFT Data for Better Reasoning Generalization

arXiv:2605.26924v1 Announce Type: new Abstract: Large language models (LLMs) have achieved remarkable progress, with post-training playing a crucial role in enhancing their reasoning capabilities. Amo

LEC: Linear Expectation Constraints for Selection-Conditioned Risk Control in Selective Prediction and Routing Systems

arXiv:2512.01556v3 Announce Type: replace Abstract: Foundation models often generate unreliable answers, while heuristic uncertainty estimators fail to fully distinguish correct from incorrect outputs

Left-Right Symmetry Breaking in CLIP-style Vision-Language Models Trained on Synthetic Spatial-Relation Data

arXiv:2601.12809v2 Announce Type: replace-cross Abstract: Spatial understanding remains a key challenge in vision-language models. Yet it is still unclear whether such understanding is truly acquired,

LiM-YOLO: Less is More with Pyramid Level Shift for Ship Detection in Optical Remote Sensing

arXiv:2512.09700v3 Announce Type: replace Abstract: General-purpose object detectors face fundamental structural limitations when applied to ship detection in satellite imagery, where the ship scale d