Search: “research”

Group Preference Collapse in Personalized Multimodal Large Language Models

arXiv:2607.22603v1 Announce Type: new Abstract: Personalized multimodal large language models (MLLMs) aim to generate user-specific responses, but existing methods mainly rely on profile-level informa

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

HandSCS: Structural Coordinate Space for Animatable Hand Gaussian Splatting

DGX agent

arXiv:2503.14736v3 Announce Type: replace Abstract: Photorealistic and animatable hand avatars are essential for applications such as AR/VR, gaming, and telepresence. Recent 3D Gaussian Splatting (3DG

researcharxiv-cs-cv

28 Jul 2026

Head Avatars with Dynamic Explicit Hair

arXiv:2607.23861v1 Announce Type: new Abstract: We present DynHair, a novel method for tracking and modeling dynamic hair for human head avatars. From video input, we reconstruct a dynamic head avatar

Hierarchical Grading in Large Language Models

arXiv:2607.22757v1 Announce Type: cross Abstract: We introduce Graded Large Language Models (GLLMs), an algebraic framework that equips the representation space of a transformer with a grading and pro

HistoGPA: A Context-Conditioned Gene-Prior Attention Framework for Histology-Based Spatial Gene Expression Prediction

arXiv:2607.24364v1 Announce Type: new Abstract: Predicting spatial gene expression from routine hematoxylin and eosin (H&E) images provides a practical complement to experimental spatial transcriptomi

Histopathological Spectrum-Guided Prostate Stratification via Segmentation-Assisted Diagnostic Transformer

arXiv:2607.22703v1 Announce Type: new Abstract: Prostate cancer diagnosis with multiparametric MRI (mpMRI) is commonly based on PI-RADS assessment or binary classification, which suffer from subjectiv

HiTMS: A High-Throughput Multi-Stream Linguistic Steganography Framework

arXiv:2607.23597v1 Announce Type: cross Abstract: Generative linguistic steganography conceals secret bits within the sampling randomness of large language models. Existing schemes are single-stream,

How Well Can AI Generate Backlogs from App Mockups?

arXiv:2607.22902v1 Announce Type: new Abstract: Creating sprint backlogs requires considerable effort, as items such as epics, user stories, and tasks can be missed or inconsistently specified. We pro

HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering

arXiv:2607.22597v1 Announce Type: new Abstract: Multi-hop question answering requires systems to retrieve evidence from multiple documents and connect scattered facts into a coherent reasoning process

IB-Flow: Information Bottleneck-Guided CFG Distillation for Few-Step Text-to-Image Generation

arXiv:2607.09133v2 Announce Type: replace-cross Abstract: While large-scale text-to-image generative models have achieved unprecedented visual performance, their inherent reliance on multi-step iterat

Image Inpainting via Stochastic Dynamics

arXiv:2607.24140v1 Announce Type: new Abstract: Image inpainting aims to recover missing regions while preserving structural consistency. We propose a non-parametric method without network training ba

Imprompt: A Language Framework for Prompt Programming

arXiv:2607.22683v1 Announce Type: new Abstract: With the unprecedented success of Language Models (LMs), the science of Prompt Engineering has evolved the powerful idea of Prompt Programming, where pr

Inference-Time Consensus for Mitigating Hidden Behaviors from LLM Fine-Tuning

arXiv:2607.23394v1 Announce Type: new Abstract: Recent work shows that fine-tuning language models on even a small amount of poisoned data can install targeted misbehavior, and ostensibly benign data

INSIGHT: Spatially resolved survival modelling from routine histology crosslinked with molecular profiling reveals prognostic epithelial-immune axes in stage II/III colorectal cancer

arXiv:2512.22262v2 Announce Type: replace-cross Abstract: Routine histology contains rich prognostic information in stage II/III colorectal cancer, much of which is embedded in complex spatial tissue

Interpreting Quantum Learning Models via Stochastic Processes

arXiv:2607.17327v2 Announce Type: replace-cross Abstract: Quantum machine learning models define probabilistic input--output maps through coherent quantum evolution and measurement. While such models

Joint Flow Matching for Generator-Consistent Classification

arXiv:2607.23946v1 Announce Type: new Abstract: We introduce Joint Flow Matching (JFM), a training framework for continuous normalising flows over multiple variables. Standard flow matching transports

Joint Optimization for Greedy Longest-match Tokenization

arXiv:2607.23362v1 Announce Type: new Abstract: Recent work has shown that subword vocabularies can be trained to optimize compression for a specific inference rule rather than relying on greedy heuri

Agents

KG2Code: Bridging Knowledge Graphs and Large Language Models via Executable Code for Question Answering

arXiv:2607.22652v1 Announce Type: new Abstract: Recent research has explored the integration of knowledge graphs (KGs) with large language models (LLMs) to enhance their performance on downstream know

agentsarxiv-cs-ai

Kinship Verification through a Forest Neural Network

arXiv:2504.18910v2 Announce Type: replace-cross Abstract: Early methods used face representations in kinship verification, which are less accurate than joint representations of parents' and children's

LA-RL: Label-Aware Self-Reflection for Reinforcement Learning in Information Extraction

arXiv:2607.23420v1 Announce Type: new Abstract: Large language models show strong promise for information extraction (IE), but existing reflection-based correction methods are often misaligned with st

LanteRn: Latent Visual Structured Reasoning

arXiv:2603.25629v2 Announce Type: replace Abstract: While language reasoning models excel in many tasks, visual reasoning remains challenging for current large multimodal models (LMMs). As a result, m

Latent Confounded Causal Discovery via Lie Bracket Geometry

arXiv:2606.19610v2 Announce Type: replace-cross Abstract: We study causal discovery from observational and interventional regimes when latent variables may affect the measured system. Our first algori

Latent-LoRA: Compact Latent-Space Adapters with Gradient-Free Routing for Continual Learning

arXiv:2607.23837v1 Announce Type: cross Abstract: Large language models generalize well to individual tasks but lack an inherent mechanism for learning them sequentially, leading to catastrophic forge

Learning from the Descent Direction: Adaptive Gradient Descent under One-Sided Holder Regularity

arXiv:2607.22906v1 Announce Type: new Abstract: We study adaptive gradient descent for continuously differentiable, possibly nonconvex objectives under one-sided Holder regularity. Unlike classical Ho

Learning switched non-linear dynamical systems from a single trajectory

arXiv:2607.23502v1 Announce Type: cross Abstract: We study empirical risk minimization for learning non-linear dynamical systems whose transition dynamics may switch over time. Under stability assumpt

Learning to Optimize at Scale: A Benders Decomposition-TransfORmers Framework for Stochastic Combinatorial Optimization

arXiv:2607.22550v1 Announce Type: cross Abstract: We propose a learning-augmented Benders decomposition framework to solve large-scale two-stage stochastic mixed-integer programs. We focus on the two-

Learning to Optimize: Joint Routing and Flow Allocation on Sparse Non-Euclidean Networks

arXiv:2607.23467v1 Announce Type: new Abstract: We study an integrated pickup-and-delivery problem on sparse, non-Euclidean networks that jointly optimizes cyclic routing, cargo flow allocation, and c

LEDOM: Reverse Language Model

arXiv:2507.01335v4 Announce Type: replace-cross Abstract: Autoregressive language models are trained exclusively left-to-right. We explore the complementary factorization, training right-to-left at sc

LEX-EC: A Lexical Evidence-Channel Audit Framework for Zero-Shot LLM Personality Classification in Black-Box Settings

arXiv:2607.24435v1 Announce Type: cross Abstract: Large language models may easily assign personality labels from text, but model interpretability remains an open problem. To address this gap, we intr

Model Releases

LIBMoE: A Library for comprehensive benchmarking Mixture of Experts in Large Language Models

model-releasesarxiv-cs-ai

arXiv:2411.00918v5 Announce Type: replace-cross Abstract: Mixture of experts (MoE) architectures have become a cornerstone for scaling up and are a key component in most large language models such as

LLM-Based vs. Lexicon-Based Sentiment Signals for Tail-Risk Detection in Meme Stocks

arXiv:2607.24072v1 Announce Type: new Abstract: This paper presents an empirical comparison of lexicon-based and Large Language Model (LLM)-based sentiment analysis for extracting market-relevant sign

Local Regularization Does Not Characterize Multiclass PAC Learnability

arXiv:2607.23449v1 Announce Type: new Abstract: Local regularization assigns each hypothesis a test-point-dependent score and predicts with a minimum-score hypothesis consistent with the sample. Asili

Logit-Coordinate Generative Models for Mixed Continuous-Categorical Tabular Data

arXiv:2607.23348v1 Announce Type: cross Abstract: Mixed continuous--categorical data pose a representation problem for continuous generative models. Flow Matching and Gaussian diffusion operate in Euc

Loss-Aware Feature-Map Pruning in Convolutional Neural Networks Using Multi-Armed Bandits

arXiv:2607.22564v1 Announce Type: new Abstract: Convolutional neural networks often contain redundant feature maps that increase storage and inference cost. This paper presents a loss-aware feature-ma

Machine Learning for Cloud Detection in IASI Measurements: A Data-Driven SVM Approach with Physical Constraints

arXiv:2508.10120v2 Announce Type: replace-cross Abstract: Cloud detection is fundamental for the interpretation and operational exploitation of hyperspectral infrared sounders, yet the capability of i

Safety

Making Mathematical Knowledge Explainable, Accessible and Interoperable Through Large Language Model Integration

arXiv:2607.24512v1 Announce Type: new Abstract: Mathematical models are central to formalizing research problems, yet their documentation often falls short of FAIR principles. Knowledge bases such as

safetyarxiv-cs-ai

Manifold-Constrained Noise Optimization for Diverse Diffusion Sampling

arXiv:2607.23937v1 Announce Type: new Abstract: Few-step distilled diffusion models generate high-quality images quickly, but often lose per-prompt diversity, producing near-identical samples across r

MAPLE: Efficient and Diverse Multi-Alpha Generation for Portfolio Construction

arXiv:2607.24131v1 Announce Type: new Abstract: Classical alpha mining achieves strong risk-adjusted returns by combining many low-correlated predictive signals, yet deep learning stock-ranking method

Masked Distillation: Internalizing the Chain-of-Thought in Language Models

arXiv:2607.22629v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) produce long, explicit chains of intermediate steps before generating a final answer at inference time. These intermediate

Model Releases

Measuring Negative Campaigning across Languages with Large Language Models: A Study of 18 Million Tweets in 19 Countries

model-releasesarxiv-cs-cl

arXiv:2507.17636v2 Announce Type: replace Abstract: Negative campaigning is a defining feature of electoral competition, yet comparative research on its drivers has remained limited by the high cost a

MEMOIR: Temporal Behavioral Memory for Recommendation Across the Preference-Drift Spectrum

arXiv:2607.23986v1 Announce Type: cross Abstract: We propose MEMOIR, a framework that segments user interaction histories into temporal windows, generates semantic behavioral memory for each period us

MemVLN: Episodic and Procedural Memory for Vision-and-Language Navigation

arXiv:2607.23504v1 Announce Type: new Abstract: Vision-and-Language Navigation in Continuous Environments (VLN-CE) requires agents to maintain long-horizon visual history for trajectory consistency wh

Metamorphic Testing for Clinical ML Models: A Framework Proposal and Pilot Study

arXiv:2607.22984v1 Announce Type: cross Abstract: Machine learning models for clinical prediction tasks, such as in-hospital mortality and sepsis onset, routinely achieve high AUROC scores. However, A

Metric Surface Reconstruction of Neurosurgical Scenes from Monocular Operating Microscope Images and Microscope Pose

arXiv:2607.22773v1 Announce Type: cross Abstract: Objective: We evaluated whether metric 3D geometry of neurosurgical operative exposure can be recovered from standard monocular operating-microscope i

Mini-batch Noise Lowers Sharpness via Dominant-Subspace Fluctuations

arXiv:2607.23012v1 Announce Type: new Abstract: During SGD training, the gradients often align strongly with the dominant subspace spanned by the top-k eigenvectors of the Hessian of the loss. While t

Minimax Lower Bounds of Kernel Discrepancy Estimation: MMD, HSIC, KSD

arXiv:2607.24235v1 Announce Type: cross Abstract: Over the past 20 years, kernel discrepancies have been leveraged as a highly powerful tool for quantifying the disagreement of distributions, with num

MiSS: A Logic-Driven Explanation of Minimal Sufficient Coalitions for Point Cloud Classifiers

arXiv:2607.24074v1 Announce Type: new Abstract: We present MiSS, a black-box, query-based framework for explaining 3D point cloud classifiers through perturbation-relative sufficiency reasoning. MiSS

ML-based Predictive Models for Power Consumption in Virtualised O-RANs

arXiv:2607.24256v1 Announce Type: cross Abstract: As communication networks adopt virtualized and disaggregated architectures, achieving energy efficiency has become increasingly important for both ec