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arXiv:2610.10919v1 Announce Type: cross Abstract: Despite decades of data quality (DQ) research, a gap remains between DQ dimensions, such as accuracy or completeness, which the literature defines in

tutorialsarxiv-cs-lg

Improving Image-Based Nutrition Estimation Through Multimodal Food-Item Verification and Recovery

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DGX agent

arXiv:2610.11144v1 Announce Type: cross Abstract: Single-image nutrition estimation can fail silently when visible foods are missed. Even when a food is correctly identified, its proposed region may n

researcharxiv-cs-ai

9 Oct 2026

In-Ride Alcohol-Impairment Detection in E-Scooterists with False-Alarm Control

arXiv:2610.11783v1 Announce Type: new Abstract: Shared e-scooter services have become a widely adopted urban transport mode. While most users ride responsibly, alcohol intoxication stands out among th

Incremental Open-Ended Deep Research with Structured Harness

arXiv:2610.11566v1 Announce Type: new Abstract: Existing Open-Ended Deep Research (OEDR) systems primarily generate reports from scratch, making them inefficient for scenarios where research reports n

Informationally Decoupled Trajectory Design for Sim-to-Real System Identification

model-releasesarxiv-cs-ro

arXiv:2610.10905v1 Announce Type: new Abstract: Sampling-based system identification estimates physically meaningful parameters by tuning a simulator to reproduce the target system dynamics, providing

Instance-anchored interaction evidence: Grounding robot plans in human pointing and handling

model-releasesarxiv-cs-ro

arXiv:2610.12157v1 Announce Type: new Abstract: A robot that assists people must often act on what a person has shown rather than said: which of several identical cartons was pointed at, or which box

Instruction-Conditioned Electromagnetic Spectrum Understanding via Budget-Adaptive Signal Tokenization

arXiv:2610.12142v1 Announce Type: new Abstract: Electromagnetic spectrum monitoring increasingly requires flexible analysis beyond task-specific recognition and detection. Multimodal large language mo

IntactWorld: Joint World Modeling with Intact Features

model-releasesarxiv-cs-cv

arXiv:2610.11174v1 Announce Type: new Abstract: While recent video generation models synthesize highly realistic visuals, they lack a genuine understanding of intrinsic real-world logic. Existing meth

Intent Graph: Navigating the Analytical Reasoning Space for Exploratory Data Analysis

arXiv:2610.11025v1 Announce Type: cross Abstract: Exploratory data analysis (EDA) is rarely open-ended in practice: analysts work from high-level domain questions toward the concrete analyses that can

Internalizer: Portable Context-to-Parameter Mapping for Very Large Language Models

model-releasesarxiv-cs-ai

arXiv:2610.11715v1 Announce Type: new Abstract: Hypernetworks that map a context directly to a LoRA adapter let a large language model carry that context in its weights, but prior work has demonstrate

Interpretable Memory Models for Spaced Repetition

arXiv:2610.10548v1 Announce Type: cross Abstract: Spaced repetition software schedules reviews with a memory model fit to review logs. Accuracy on a test set is not sufficient evidence of quality sinc

Interval-valued SHAP in Tree-Based Models

arXiv:2610.11953v1 Announce Type: new Abstract: Shapley values are among the most popular feature-attribution explanations. Efficient approaches for computing/estimating Shapley values for tree-based

Agents

Intervention anchors and scientific verification in synthetic vascular predictive representations

arXiv:2610.11704v1 Announce Type: new Abstract: Complete orthogonal predictive coordinates do not by themselves bind a latent direction to a named intervention. We present a mathematical and synthetic

agentsarxiv-cs-ai

InterviewPlayground: A Simulation Environment for Evaluating AI Interviewers

arXiv:2610.12023v1 Announce Type: new Abstract: Increasingly, AI interviewers are being developed to elicit open-ended responses in applications like market research, public polling, preference elicit

IntrinSync: Joint Intrinsic Decomposition and Reciprocal Rendering

arXiv:2610.11138v1 Announce Type: new Abstract: Inverse rendering decomposes an image into intrinsic properties such as appearance, illumination, geometry, and material, yet these properties are inher

researcharxiv-cs-cv

Invariant-Measure Reasoners: Stable Representations for Latent Reasoning

arXiv:2610.10996v1 Announce Type: new Abstract: Latent reasoning models repeatedly update a latent state using the same recurrent block. As the recurrent depth increases, the sequence of latent states

IS-Diff: Improving Diffusion-Based Inpainting with Better Initial Seed

arXiv:2509.11638v2 Announce Type: replace Abstract: Diffusion models have shown promising results in free-form inpainting. Recent studies based on refined diffusion samplers or novel architectural des

researcharxiv-cs-cv

Is In-Domain Training Enough for Fine-Grained Industrial Anomaly Understanding?

model-releasesarxiv-cs-cv

arXiv:2610.12310v1 Announce Type: new Abstract: A single multimodal large language model (MLLM) struggles to excel simultaneously at detection, localization, description, and reasoning in multimodal i

Is Memorization Context-Sensitive? Prefix-Based Extraction Beyond Isolated Prefixes

arXiv:2610.12085v1 Announce Type: new Abstract: Large language models (LLMs) can expose memorized training sequences under prefix-based extraction: given a prefix from a training example, the model ma

Is Peer Review Really in Decline? Analyzing Review Quality across Venues and Time

arXiv:2601.15172v2 Announce Type: replace Abstract: Peer review is at the heart of modern science. As submission numbers rise and research communities grow, the decline in review quality is a popular

Applications

Is Real-World Training Data Necessary for Generalist Graph Anomaly Detection?

arXiv:2610.12167v1 Announce Type: new Abstract: Generalist graph anomaly detection (GAD) aims to build a foundation model that detects anomalies on arbitrary unseen graphs without retraining or fine-t

applicationsarxiv-cs-lg

Applications

ISBO: Scalable Spatio-Temporal Bayesian Optimization with Log Gaussian Cox Process Models via the INLA-SPDE Approach

arXiv:2610.12213v1 Announce Type: cross Abstract: Bayesian Optimization (BO) is a popular method for efficiently optimizing expensive black-box objectives. However, BO utilizing standard Gaussian Proc

applicationsarxiv-cs-lg

It's Always 10:10: Reference Images Break a Bias That Prompts Only Dent

arXiv:2610.11320v1 Announce Type: new Abstract: Text-to-image models appear to reproduce the habits of the photographs they learned from. Analog clocks are an extreme case: in advertising, watches alm

safetyarxiv-cs-cv

JevForest: Path Voting for Budgeted Feature Acquisition

arXiv:2610.10615v1 Announce Type: cross Abstract: Choosing which information to observe is central to prediction under limited observation budgets. We study JevForest, a feature acquisition policy tha

safetyarxiv-cs-lg

Just Weather Scoring: Efficient End-to-end Nowcasting with Distributional Diffusion

arXiv:2610.12189v1 Announce Type: cross Abstract: Generative diffusion models are well-suited for probabilistic precipitation nowcasting, but existing approaches often rely on separately trained compr

researcharxiv-cs-cv

KDFP: A first-principles approach to knowledge distillation in large language models

model-releasesarxiv-cs-lg

arXiv:2610.10854v1 Announce Type: new Abstract: Knowledge distillation is an established technique for improving the capabilities of small, efficient student models by training them with the represent

La-Ribo: RNA Co-Design via Geometry-Latent Flow Matching

arXiv:2610.12236v1 Announce Type: cross Abstract: RNA function arises from the coupling of nucleotide sequence and three-dimensional structure, motivating their joint design. Coordinating global foldi

LadderEdit: Edit-Level Residual Compression for Memory-Efficient Lifelong Editing of LLMs

model-releasesarxiv-cs-cl

arXiv:2610.11160v1 Announce Type: new Abstract: Lifelong editing of LLMs requires storing thousands of edits after acquisition. A widely used family of approaches attaches one LoRA adapter per edit, w

LAIR-Net: Leaky Alignment-Impulse Residual Networks for Tabular Regression

model-releasesarxiv-cs-lg

arXiv:2610.11538v1 Announce Type: cross Abstract: Deep randomized models fix hidden-layer parameters through random initialization and learn only closed-form readouts, typically adding depth by stacki

Lamarck's Driving School: Discovering Autonomous Driving Training Strategies through Evolutionary Competition

arXiv:2610.11662v1 Announce Type: new Abstract: Autonomous driving capabilities depend strongly on the distribution of scenarios encountered during training. Existing methods commonly construct or dyn

safetyarxiv-cs-ai

Language Modeling is Monotone Compression

arXiv:2610.11031v1 Announce Type: cross Abstract: A long-standing hypothesis in artificial intelligence and neuroscience posits that intelligence is closely related to compression: the ability to comp

Hardware

Language Models as AI Research World Models

arXiv:2610.12235v1 Announce Type: new Abstract: AI research agents automate the cycle of proposing, implementing, and evaluating experiments, opening a path toward recursive self-improvement. Yet thei

hardwarearxiv-cs-cl

Language Models for Page-Level Layout Decisions in E-commerce Search

arXiv:2610.10920v1 Announce Type: cross Abstract: E-commerce search pages are critical touchpoints for millions of online shoppers. While traditional search engines return a ranked list of results, mo

Language-Specific Effects of Tokenizer Choice in Multilingual Language Models

arXiv:2610.12144v1 Announce Type: new Abstract: Tokenizer choice affects multilingual language modeling, but vocabulary capacity is finite and vocabulary size is often constrained: improving represent

Tutorials

Lapras: Latent Reasoning for Time Series Language Models

arXiv:2610.11111v1 Announce Type: new Abstract: Time Series Language Models (TSLMs) offer a promising path toward time series understanding by reasoning over temporal signals and producing natural lan

tutorialsarxiv-cs-cl

Local Ai

Large Language Model-Assisted Preparation of Transportation Management Plans: A Case Study with WisDOT WisTMP System

arXiv:2610.10650v1 Announce Type: new Abstract: Work zones are critical yet hazardous components of transportation infrastructure, requiring carefully designed Transportation Management Plans (TMPs) t

local-aiarxiv-cs-cl

Large Language Model Turnover Undermines Screening for Artificial Intelligence-Assisted Scientific Writing

model-releasesarxiv-cs-ai

arXiv:2610.11599v1 Announce Type: cross Abstract: Journals and conferences have begun to screen submitted manuscripts for text written using large language models (LLMs). The reliability of this scree

Large Language Models for Machine Translation Quality Annotation: Humans and Models Are Both Challenged

arXiv:2610.10918v1 Announce Type: new Abstract: Large Language Models (LLMs) are considered to be a more efficient and cost-effective alternative to human judgment for Machine Translation (MT) evaluat

Large-Scale Benchmarking of Quantum Neural Network Configurations for Financial Time Series Forecasting

model-releasesarxiv-cs-lg

arXiv:2610.12148v1 Announce Type: new Abstract: Quantum machine learning, and quantum neural networks (QNNs) in particular, are advancing fields with growing potential. Although systematic comparisons

Latent Core Tokenizer: Compress, but Meaningfully

arXiv:2610.12376v1 Announce Type: new Abstract: Tokenizers are commonly optimized for compression, but a compact vocabulary does not necessarily distribute its capacity evenly across languages. We int

Leakage-Controlled Multimodal Learning for Diagnosis and Progression Prediction in Alzheimer's Disease Research

arXiv:2610.10648v1 Announce Type: new Abstract: Alzheimer's disease prediction involves irregular visits, heterogeneous measurements and incomplete modalities. This study presents a multimodal multita

Applications

Learned Image Compression for Vision-Language-Action Models

arXiv:2606.16253v2 Announce Type: replace-cross Abstract: Vision-language-action (VLA) models increasingly rely on high-frequency multi-camera observations, making visual communication a major bottlen

applicationsarxiv-cs-ai

Tutorials

Learning from Hetero Density for Cryo-EM Protein Reconstruction

arXiv:2610.11403v1 Announce Type: new Abstract: Reconstructing protein structures from cryo-electron microscopy (cryo-EM) maps is essential for understanding macromolecular assemblies. Although learni

tutorialsarxiv-cs-lg

Learning from Own Solutions: Self-Conditioned Credit Assignment for Reinforcement Learning with Verifiable Rewards

arXiv:2606.18810v2 Announce Type: replace-cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has driven substantial progress in training LLMs for reasoning tasks, but representative

safetyarxiv-cs-ai

Learning How to Search for Plans with Exponentially Less Space

arXiv:2610.10954v1 Announce Type: new Abstract: Heuristic search for a plan can store exponentially many states, even when its heuristic is almost perfect. We instead learn search control, one specifi

safetyarxiv-cs-ai

Learning infinite context windows in recurrent architectures via spatial neural computing

arXiv:2610.10690v1 Announce Type: new Abstract: Recurrent neural networks (RNNs) offer linear-time scaling with sequence length while requiring only constant memory, yet they struggle to capture long-

Local Ai

Learning Kilometer-Scale Weather Prediction with Global-Regional Alignment

arXiv:2610.12401v1 Announce Type: new Abstract: Kilometer-scale regional weather forecasting is essential for local weather warnings and weather-sensitive decisions. Existing data-driven approaches of

local-aiarxiv-cs-lg

Learning Language-Conditioned Traversability Representations for Adaptive Visual Navigation

arXiv:2610.11622v1 Announce Type: new Abstract: Traversability is essential for visual navigation but varies with robot capabilities and user preferences. Conventional pipelines often rely on explicit

researcharxiv-cs-ro