Search: “research”

Convergence of Stochastic Gradient Methods under Heavy-Tailed Noise and Holder Smoothness

arXiv:2609.12785v1 Announce Type: new Abstract: Classical convergence guarantees for stochastic gradient methods typically assume Lipschitz-smooth objectives and finite-variance gradient noise, both f

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Research

Creating an Atomic User Model for Personality-Aware Large Language Model Interaction

DGX agent

arXiv:2609.12086v1 Announce Type: cross Abstract: Assistants built on large language models are expected to write as their user would, and the dominant approach is single-channel: preferences summaris

researcharxiv-cs-cl

14 Sept 2026

CRFCAN: A Complex-Valued Cross-Domain Residual Network for Joint Channel and Phase Noise Estimation in Sub-THz OFDM Systems

arXiv:2609.12244v1 Announce Type: new Abstract: In sub-terahertz (sub-THz) communications, the coupling of ultra-wide bandwidth and severe phase noise (PN) impairments renders conventional joint chann

CueMem: Cue-Guided Context Reconstruction for Long-Term Conversational Memory

arXiv:2609.12354v1 Announce Type: new Abstract: Long-term conversational agents must answer user queries by recalling information from extended dialogue histories, yet directly using the full history

DATAFARM: Distribution-Aligned Task and Motion Planning for Fine-Tuning Vision-Language-Action Models

arXiv:2609.12316v1 Announce Type: new Abstract: Collecting high-quality robot data remains a fundamental challenge for training robot foundation models. Task and motion planning (TAMP) offers a scalab

researcharxiv-cs-ro

Decentralized Evolution of Hexapod Gaits with Independent Leg Controllers

arXiv:2609.12400v1 Announce Type: cross Abstract: This paper presents a novel approach to hexapod locomotion by evolving each leg's gait independently through a decentralized evolutionary algorithm. U

researcharxiv-cs-ro

DERA: Detached Edge-Residual Adaptation for Prohibited item Detection

arXiv:2609.12411v1 Announce Type: new Abstract: Prohibited-item detection in X-ray imagery remains challenging due to object superposition, weak texture, and material clutter which obscure both semant

Dimension-Corrected Hitting Times for Heavy-Tailed Spectral Emergence in Neural Optimizer Dynamics

arXiv:2609.12994v1 Announce Type: new Abstract: Heavy-tailed empirical spectral densities of neural-network weight matrices are widely used as diagnostics of implicit self-regularization, but the step

Direct Topology Tracking in Continuous Implicit Models

arXiv:2609.12157v1 Announce Type: cross Abstract: We present a framework for tracking topological features directly within continuous implicit models. Such models, including implicit neural representa

Does Video Memory Use What It Retrieves? A Causal Audit of Memory Specificity

arXiv:2609.12090v1 Announce Type: new Abstract: Video models increasingly use memory to preserve information over long sequences, with the assumption that gains come from retrieving and using the corr

DRDN: Decoupled Representation Dynamic Network for From-Scratch ViT Class-Incremental Learning

arXiv:2607.01630v2 Announce Type: replace Abstract: Dynamic expansion methods for class-incremental learning (CIL) protect task-specific knowledge by growing dedicated tokens or subnetworks, yet our a

Exact ReLU realization of binary affine refinement iterates via reflection folding and cone switching

arXiv:2609.11962v1 Announce Type: cross Abstract: We study vector-valued binary affine refinement operators with finitely supported matrix masks and compactly supported continuous piecewise linear inp

Explainable Prediction from Mobile Sensing Data through LLM-guided Concept Integration

arXiv:2609.11995v1 Announce Type: new Abstract: Mobile sensing enables longitudinal monitoring of behavioral and physiological patterns in everyday settings. However, accurate prediction remains chall

Explaining Time Series Forecasting with Horizon-Resolved Attribution

arXiv:2609.12639v1 Announce Type: new Abstract: Recent advances in explaining time series (TS) models have produced methods that identify which past values a prediction depends on. However, most exist

Explanations-Driven Active Feature Acquisition for Algorithmic Recourse

arXiv:2609.12179v1 Announce Type: new Abstract: Algorithmic recourse methods typically assume that a predictive model has access to all features of an individual. In practice, decisions are often made

Fast and Faithful: Principled Conditional Flow Matching for Inverse Problems

arXiv:2609.12953v1 Announce Type: new Abstract: Flow matching approaches to imaging inverse problems commonly incorporate measurements in two ways. Conditioning-based approaches supply measurement-der

Fast BIB simulation at a future Muon Collider with generative machine learning

arXiv:2609.12054v1 Announce Type: cross Abstract: Beam-induced background (BIB) from muon decay products will be an overwhelming and unavoidable background at a future Muon Collider. In order to devel

Fewer Words, Not Fewer Tokens: Measuring the Sanskrit Tokenization Penalty per Proposition

arXiv:2609.12960v1 Announce Type: new Abstract: Sanskrit fuses case, number, person and tense into word endings and chains clauses into compounds, so it is information-dense per word. Whether that den

Model Releases

FINESSE: An Agent-Based Simulator and Benchmark Dataset for Multimodal Financial Event Sequences

model-releasesarxiv-cs-lg

arXiv:2609.11993v1 Announce Type: new Abstract: Machine learning research in financial services is limited by the scarcity of representative open-source datasets. Existing resources are often narrowly

GLaMoR: Consistency Checking of OWL Ontologies using Graph Language Models

arXiv:2504.19023v2 Announce Type: replace-cross Abstract: Semantic reasoning aims to infer new knowledge from existing knowledge, with OWL ontologies serving as a standardized framework for organizing

Global Path Planner with Multi-Model Switching

arXiv:2609.13015v1 Announce Type: new Abstract: This work enhances global path planning via a pure-pursuit controller with multi-model kinematic switching that sustains plan fidelity across diverse te

researcharxiv-cs-ro

Guided Adversarial Robust Transfer Learning with Source Mixing

arXiv:2309.06534v2 Announce Type: replace Abstract: Transfer learning is a critical technique that enables the application of knowledge gained from existing tasks or domains to improve performance on

HemaHier: Chain-Conditioned Ordinal Hierarchies for Lineage-Aware Bone-Marrow Cytology

arXiv:2609.12835v1 Announce Type: new Abstract: Bone-marrow cytology is inherently structured: each cell belongs to a hematopoietic lineage, and many cell types lie on ordered maturation trajectories.

High-Probability Convergence of SGD via Batched Updates

arXiv:2609.12765v1 Announce Type: cross Abstract: Stochastic gradient descent (SGD) is the primary workhorse for large-scale optimization. While the average behavior of its iterates, typically charact

HSI-Road Relabeled: Surface-Aware Road-Scene Segmentation

arXiv:2609.12151v1 Announce Type: new Abstract: The HSI-Road dataset provides paired RGB and 25-channel NIR (600--960~nm) images with binary masks but no surface-level labels.~This paper introduces a

Hurdle-RMIL: Addressing Zero Inflation and Long-Tailed Imbalance in Infrared Rainfall Retrieval

arXiv:2510.20486v2 Announce Type: replace Abstract: Imbalanced labels can cause frequent samples to dominate AI-based quantitative remote sensing, degrading rare-event retrieval. In rain-rate retrieva

I Am No One: Style-Aware Paraphrasing for Text Anonymization

arXiv:2609.12341v1 Announce Type: new Abstract: Authorship attribution models can re-identify users from seemingly anonymized text by exploiting stable stylistic fingerprints, even after explicit iden

Impact of Multiple Non-Invasive Biosignals on Cardiovascular Biomarker Estimation via Simulation-Based Inference

arXiv:2609.11969v1 Announce Type: cross Abstract: As the population ages, the number of patients with cardiovascular diseases continues to increase, highlighting the need for early detection before pr

IMPLY: Physically Anchored Consistency for World-Model Rollouts

arXiv:2609.12441v1 Announce Type: cross Abstract: A world model asked what happens if an object is pushed at several speeds produces several futures. If the model has the object in mind, those futures

In-Hospital Stroke Risk-State Classification from PPG-Derived Hemodynamic Features

arXiv:2602.09328v2 Announce Type: replace Abstract: The scarcity of temporally aligned pre-event physiological data limits the study of stroke risk states before documented clinical recognition. We fo

Inference for Newton Methods with Accelerated Sketch-and-Project via Random Scaling

arXiv:2609.12421v1 Announce Type: cross Abstract: We study an online sketched Newton method that approximates the Newton direction at each step via a state-of-the-art sketching solver, called the gene

Information-Induced Training Geometry: Exact Reduction, Canonical Completion, and Structured Expressivity

arXiv:2609.12991v1 Announce Type: new Abstract: Training data constrains optimizer geometry through the covectors visible to a declared information channel. We study how such partial information deter

Investigating Temporal Motion Features for Pose-to-Text Indian Sign Language Translation

arXiv:2609.12993v1 Announce Type: cross Abstract: We investigate the effect of pretrained T5 model scale and explicit motion features on pose-to-text Indian Sign Language Translation (SLT) for the WSL

Is Multilingual LLM Watermarking Truly Multilingual? Scaling Robustness to 100+ Languages via Back-Translation

arXiv:2510.18019v3 Announce Type: replace Abstract: Multilingual watermarking aims to make large language model (LLM) outputs traceable across languages, yet current methods still fall short. Despite

Judging by the Cover: Cleaning LLM Truthfulness Benchmarks to Avoid Surface-Level Feature Leakage

arXiv:2609.13003v1 Announce Type: new Abstract: Binary-choice truth benchmarks ask models to choose between a correct and an incorrect answer, but if the two answers differ systematically in surface-l

Kraken: LLM-based Speech-to-Speech Translation via Low-bitrate VQ and Dual-path Source Conditioning

arXiv:2609.13045v1 Announce Type: new Abstract: Speech-to-speech translation (S2ST) has advanced significantly with speech LLMs, offering the potential for joint optimization and preserving non-lingui

Language Is an Insufficient Substrate for Quantitative Reasoning, and Consequential Domains Need Large Quantitative Models

arXiv:2609.12105v1 Announce Type: cross Abstract: The prevailing assumption in applied machine learning is that progress on consequential quantitative decisions such as pricing risk, allocating capita

LatentVerse: A Framework for Understanding Shared and Modality-Specific Information in Multimodal Latent Representations

arXiv:2609.12364v1 Announce Type: new Abstract: Latent embeddings have become a central data abstraction in modern machine learning, especially in biomedicine, where foundation models are increasingly

Learning Interaction Kernels from Collective Steady States

arXiv:2609.12004v1 Announce Type: cross Abstract: We propose a learning procedure for system identification in interacting particle systems from single-snapshot observations of collective behaviors, u

Learning the Geometry of Collider Events with Metric-Aware Deep Sets

arXiv:2609.12024v1 Announce Type: cross Abstract: Optimal transport gives structured data a geometry, but exact evaluation is costly in large pairwise analyses that exploit relationships among distanc

LLM-Enhanced Dual-Branch Learning for Large-Scale Multi-Label Text Classification

arXiv:2609.12915v1 Announce Type: new Abstract: Large-scale multi-label text classification assigns a small subset of relevant labels to each document from a vocabulary containing thousands or tens of

Lumina-OmniLV: A Unified Multimodal Framework for General Low-Level Vision

arXiv:2504.04903v3 Announce Type: replace Abstract: We present Lunima-OmniLV (abbreviated as OmniLV), a universal multimodal multi-task framework for low-level vision that addresses over 100 sub-tasks

Model Releases

MAxBench: A Multinomial Concept Recovery Benchmark

model-releasesarxiv-cs-cl

arXiv:2609.13072v1 Announce Type: cross Abstract: Fine-grained control of language model behaviors (e.g., steering) is among the more actionable outcomes of interpretability research. For binary conce

Measuring Pragmatic Influence in Large Language Model Instructions

arXiv:2602.21223v2 Announce Type: replace Abstract: It is not only what we ask large language models (LLMs) to do that matters, but also how we ask them. Phrases like ``This is urgent'' or ``As your s

Membership Inference via Pairwise Likelihood Ratios

arXiv:2609.12367v1 Announce Type: cross Abstract: Membership inference attacks (MIAs) are the standard tool for auditing the privacy risks of machine learning models. Given a query point, an MIA aims

MGAvatar: Mesh-Bound Gaussians for Head Avatar Geometry and Appearance Modeling

arXiv:2609.12850v1 Announce Type: new Abstract: Accurate head modeling requires a stable yet expressive geometric representation. Existing Gaussian-based head avatars commonly rely on parametric templ

MPT: Missing Prototype Tracking via Barycentric Reconstruction in Vehicular Federated Learning

arXiv:2609.12771v1 Announce Type: cross Abstract: Cross-vehicle federated learning enables vehicles to collaboratively improve perception models while keeping locally collected driving data private. H

Observation-Anchored Selective Assimilation for Longitudinal Tumor-State Proxy Forecasting in Post-Treatment Glioma

arXiv:2609.12435v1 Announce Type: new Abstract: Post-treatment MRI in patients with glioma provides serial observations for updating patient-specific tumor-state proxy estimates, but variable appearan