Search: “research”

EnGRICH: Enhancing Generative Reward Modeling with Critiques from Humans

arXiv:2610.05370v2 Announce Type: replace Abstract: Generative reward models (GRMs) are important for LLM optimization. Unlike scalar reward models, GRMs generate natural-language critiques alongside

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Research

Enhancing High-order Interaction Awareness in LLM-based Recommender Model

DGX agent

arXiv:2409.19979v4 Announce Type: replace-cross Abstract: Large language models (LLMs) have demonstrated prominent reasoning capabilities in recommendation tasks by transforming them into text-generat

researcharxiv-cs-cl

7 Oct 2026

Model Releases

EPOCH: Reliable Discovery through Evidence-Governed Search

model-releasesarxiv-cs-ai

arXiv:2610.06986v1 Announce Type: new Abstract: AI research agents are increasingly used to search over programs, mathematical constructions, and proofs. However, existing systems typically optimize e

Event Detection in Table Tennis Videos using 2D Keypoints

arXiv:2610.08286v1 Announce Type: new Abstract: This paper addresses the challenge of automatic, frame-accurate event detection in table tennis videos. Current methods for estimating 3d ball trajector

Evolutionary One-Step Generators: Fast and Diverse Sampling for Discrete Design

arXiv:2610.08367v1 Announce Type: new Abstract: Several discrete design tasks, such as molecular discovery, require diverse collections of useful candidates at low computational cost. High validity al

Exact Calibration and Sharp Risk Geometry for Volume-Sampled Ridge Regression

arXiv:2610.07721v1 Announce Type: cross Abstract: We study ridge regression from exactly s distinct rows of a fixed design. Responses are fixed, and only the subset is random. The determinant law and

Explainable Rule Mining of IPv6 Extension-Header Presence Patterns from Paired-Vantage Captures

arXiv:2610.08090v1 Announce Type: cross Abstract: IPv6 extension headers (EHs), such as fragmentation, segment routing, and in-situ telemetry, are operationally important yetwidely dropped in transit,

Explicit Asymptotic Bounds for Sequential Calibration Beyond T^{2/3}

arXiv:2610.07623v1 Announce Type: cross Abstract: Probability forecasts are calibrated when predicted probabilities match empirical outcome frequencies: among events assigned a probability p, we'd hop

Exploiting Acoustic and Content-Oriented Speaker Verification Attacks Against Multilingual Voice Anonymization

arXiv:2610.08107v1 Announce Type: cross Abstract: Attacker ASV systems for voice anonymization have been studied primarily in English, leaving their behavior in multilingual settings largely unexplore

Fast and Efficient Asynchronous Gossip Algorithm for Robust and Non-Smooth Convex Decentralized Learning

arXiv:2601.20571v3 Announce Type: replace-cross Abstract: Asynchronous primal-dual methods for decentralized non-smooth convex optimization often require each node to maintain O(d) auxiliary variables

Fast, Interpretable, and Deterministic Time Series Classification With a Bag-of-Receptive-Fields

arXiv:2311.18029v2 Announce Type: replace-cross Abstract: The current trend in the literature on Time Series Classification is to develop increasingly accurate algorithms by combining multiple models

Feature Encoding in VAE-based Audio Decoders: Effects of Input, Depth and Distribution

arXiv:2610.07966v1 Announce Type: cross Abstract: Neural audio synthesis models like the Realtime Audio Variational autoEncoder (RAVE) achieve impressive genera tion quality, yet how their internal re

Feature Information Dynamics in Diffusion

arXiv:2610.08626v1 Announce Type: cross Abstract: Diffusion models generate data through a continuum of denoising problems, and are widely observed to reveal coarse structure before fine detail. Yet,

FedDermaSeg: Federated Learning for Dermatological Image Segmentation

arXiv:2610.08574v1 Announce Type: cross Abstract: Skin cancer is a major global health concern, and early detection and accurate lesion delineation are important for effective diagnosis and treatment

Few-Shot Bioactivity Prediction with Meta-Learning under Assay Heterogeneity

arXiv:2610.07079v1 Announce Type: new Abstract: Accurate bioactivity prediction is a central challenge in early-stage drug discovery, as individual assays often contain too few measurements to train r

Finding the Heads and the Neurons Responsible for Network Information Retrieval in Language Models

arXiv:2610.08200v1 Announce Type: new Abstract: We ask whether specific attention heads, and more finely specific neurons inside those heads, are responsible for recognizing that a language model's co

Forecasting the Growth of Social Media Information Cascades: Towards Human-in-the-Loop Misinformation Triage

arXiv:2610.07209v1 Announce Type: cross Abstract: Limited review teams must identify which emerging claims are likely to keep growing before their eventual reach is known. We center early misinformati

From Evidence to Action: How Tool-Using Agents Fail

arXiv:2610.07753v1 Announce Type: cross Abstract: Tool-using agents make consequential changes to external state, yet correct outcomes do not guarantee that their actions were supported by evidence es

From Model to Prototype: Design and Motor-Flap Propulsion Control of a Twin-Wing Metamorphic UAV

arXiv:2610.07896v1 Announce Type: new Abstract: This paper presents the design and control strategy for MetaMorpher, a metamorphic Unmanned Aerial Vehicle (UAV), capable of both spinning-wing hover an

researcharxiv-cs-ro

From Sandbox to Enforcement: Confidence-Qualified Threat Intelligence for Critical Infrastructure

arXiv:2610.07310v1 Announce Type: cross Abstract: Security operations centres and national incident-response teams defending critical infrastructure collect abundant threat data yet struggle to turn i

Generalized Matheron Variational Implicit Processes

arXiv:2610.07938v1 Announce Type: new Abstract: Implicit-process priors specify distributions over functions through sample-forward mechanisms such as Bayesian neural networks and stochastic simulator

Generative AI translations in high-stakes emergency messaging

arXiv:2610.08601v1 Announce Type: new Abstract: Emergency messaging such as extreme-weather reports and earthquake instructions can involve high stakes, to the extent that translation errors can lead

GenZ-LIO: Generalizable LiDAR-Inertial Odometry Beyond Confined--Open Boundaries

arXiv:2603.16273v3 Announce Type: replace Abstract: For field robotic missions such as inspection, search-and-rescue, and exploration, light detection and ranging (LiDAR)-inertial odometry (LIO) can s

researcharxiv-cs-ro

Global Transport Couplings for Classifier-Free Guided Flows

arXiv:2610.07555v1 Announce Type: new Abstract: Optimal-transport couplings have been shown to reduce training variance in unconditional flow models, but their role in conditional generation remains u

Industry

Google invests millions in Mark Zuckerberg’s efforts to create a ‘virtual cell’

Google DeepMind, Meta, and AI drug discovery startup Isomorphic Labs are jointly investing 300 million into Biohub, the nonprofit biomedical research organization founded by Mark Zuckerberg and his wi

industrythe-verge-ai

Hierarchy-GBP: Accelerating Factor Graph Inference via Abstraction and Recovery

arXiv:2610.06978v1 Announce Type: new Abstract: Gaussian Belief Propagation (GBP) is a distributed inference algorithm that passes messages in graphical models, making it attractive for scalable spati

High-Dimensional Statistical Inference for Sparse Support Vector Machines

arXiv:2610.08345v1 Announce Type: cross Abstract: Using a replica-symmetric high-dimensional characterization, we develop an inferential framework for sparse support vector machines when the sample si

Honesty over Accuracy: Trustworthy Language Models through Reinforced Hesitation

arXiv:2511.11500v3 Announce Type: replace Abstract: Modern language models fail a fundamental requirement of trustworthy intelligence: knowing when not to answer. Despite achieving impressive accuracy

How High Is 0.6? Floors, Ceilings, and Headroom in Interpretability Probing

arXiv:2610.08544v1 Announce Type: cross Abstract: Probes are the workhorse of interpretability. If a model's hidden states predict a variable, the model is said to represent it. But a probe score has

How Many Independent Samples Does a Satellite Image Contain? Generalization Bounds for Spatially Dependent Data

arXiv:2610.08227v1 Announce Type: cross Abstract: Machine learning classifiers for remote sensing imagery are typically evaluated as though every pixel were an independent sample. Spatial autocorrelat

How Much Planning Is Enough? Reducing Search and Computation in World-Model Planning

arXiv:2610.08350v1 Announce Type: cross Abstract: Visual world models enable goal-directed control through decision-time action search, but their deployment efficiency is often limited by conservative

Hub for Outliers, Spokes for Inliers: Uniform Latent Space Construction for Dual-Mismatched Semi-Supervised Learning

arXiv:2610.07610v1 Announce Type: new Abstract: Semi-supervised learning typically assumes that labeled and unlabeled data share an identical class distribution and label space. However, this setting

HuC-VideoMAE: Human-Centric Video Masked Autoencoding from synthetic data

arXiv:2610.08433v1 Announce Type: new Abstract: Modern action recognition models rely on video transformers pretrained on massive collections of web-crawled videos, such as Kinetics-700. However, the

HygieneRoboBench: Benchmarking Hygiene-Aware Planning for Household Robots

arXiv:2610.08642v1 Announce Type: cross Abstract: Contact with contaminated objects can spread hazards through a household robot's grippers, tools, and shared surfaces, while new contacts can make an

Hypergraph-Enhanced Dual Convolutional Network for Bundle Recommendation

arXiv:2312.11018v3 Announce Type: replace-cross Abstract: Bundle recommendation ranks sets of related items rather than isolated items. Its central challenge is to connect user preferences, item inter

Identifiability Analysis of Linear ODE Systems with Hidden Confounders

arXiv:2410.21917v3 Announce Type: replace-cross Abstract: The identifiability analysis of linear Ordinary Differential Equation (ODE) systems is a necessary prerequisite for making reliable causal inf

Illusory Pattern Perception Drives Spurious Inference in Large Language Models

arXiv:2610.07791v1 Announce Type: new Abstract: Illusory pattern perception is a well-documented human cognitive tendency to infer meaningful relationships in data that is actually random. Such a tend

Image-Space Refraction Correction for Underwater 3D Reconstruction: Warping Flat-Port Views into Pinhole Perspective

arXiv:2610.07788v1 Announce Type: new Abstract: Consumer-grade cameras in flat-port housings are widely used for underwater exploration and mapping of coral reefs and seafloor habitats due to their lo

Improving Diversity in LLM Short Story Generation

arXiv:2610.06729v2 Announce Type: replace Abstract: Large language models (LLMs) can generate accurate responses, but these are void of diversity. We attempt to address this for the task of creative s

Incidental information contaminates patient notes and disrupts clinical reasoning in large language models

arXiv:2610.08585v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly relied upon to support ambient documentation and clinical reasoning. Here we examine the impact of a failu

Inference and learning in sparse autoencoders as natural gradient flow

arXiv:2610.07389v1 Announce Type: cross Abstract: Sparse autoencoders are widely used to uncover interpretable features in neural networks, yet reliable recovery remains difficult when features overla

Information-Dense Synthesis for Molecular Discovery

arXiv:2610.08495v1 Announce Type: cross Abstract: Machine learning can accelerate molecular discovery by designing molecules and planning experiments. However, many scientific challenges demand molecu

InterCorrect: Intersection-Aware Correction of Demographic Model Merging for Fair ASR

arXiv:2610.08604v1 Announce Type: new Abstract: Automatic Speech Recognition (ASR) systems often show uneven performance across demographic groups, and errors can be especially difficult to address fo

Investigating Model Compression for Neural Machine Translation in the Biomedical Domain

arXiv:2610.07032v1 Announce Type: cross Abstract: Large-scale pretrained transformer models have achieved state-of-the-art performance across diverse machine translation tasks, including multilingual

Isotropic Yet Undecodable: The Sequential Content-Sufficiency Gap in Latent-Predictive Text Representations

arXiv:2610.07906v1 Announce Type: new Abstract: We study sequential content sufficiency by investigating whether a representation retains the ordered target information available in its input. An info

Joint upper-bound coverage and route-choice utility: an empirical evaluation on two urban proxy tasks

arXiv:2610.06995v1 Announce Type: new Abstract: Whether more accurate traffic forecasts or higher uncertainty coverage improve route decisions is unclear. We evaluate this question with a frozen proto

Knowing When to Trust a Prior: Reliability-Gated Cue Fusion for Video Gaze Prediction

arXiv:2610.08663v1 Announce Type: new Abstract: Video gaze prediction is led by gaze-trained models, yet gaze-free priors carry signal those models have not absorbed, if one knows when to trust them.

Koopman Model Predictive Control of An Origami-Inspired Soft Exoskeleton for Knee Rehabilitation

arXiv:2510.11094v2 Announce Type: replace Abstract: Knee rehabilitation plays a critical role in restoring patients' mobility and functional independence. Traditional rigid rehabilitation exoskeletons

researcharxiv-cs-ro