Search: “research”

Effects of interpulse-interval variation on deep-learning classification of bat vocalizations

arXiv:2610.02284v1 Announce Type: new Abstract: Temporal context may aid automated bat-species classification, but the contribution of specific features remains unclear. We investigated whether variat

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Research

Efficient Reasoning Training Does Not Always Harm CoT Faithfulness and Monitorability

DGX agent

arXiv:2610.03509v1 Announce Type: new Abstract: Chain-of-thought (CoT) reasoning allows humans to inspect how large language models reach their answers, and oversee model behaviour. This reasoning com

researcharxiv-cs-ai

5 Oct 2026

Emergent Structure in the Marginal Attention Space of Language Models

arXiv:2610.03109v1 Announce Type: new Abstract: While representation similarity across independently trained language models is well-documented, how internal mechanics such as attention behave across

ENCORE: Exact Non-equilibrium COntrol with Replica Exchange for Diffusion Generation

arXiv:2610.02538v1 Announce Type: cross Abstract: Inference-time control steers a pretrained generative model towards a target distribution without retraining. We study tilted targets pi_0propto G_0,p

Energy Saving in 5G and Beyond Networks: A Quantum Reinforcement Learning Approach

arXiv:2610.02403v1 Announce Type: cross Abstract: Energy saving has become a critical challenge in 5G and beyond networks. The rapid growth of connected devices has increased the overall network energ

Error Propagation in Dynamic Programming: From Stochastic Control to American Option Pricing

arXiv:2509.20239v2 Announce Type: replace-cross Abstract: This paper investigates theoretical and methodological foundations for stochastic optimal control (SOC) in discrete time. We start formulating

Estimating prevalence with precision and accuracy

arXiv:2507.06061v2 Announce Type: replace-cross Abstract: Unlike classification, whose goal is to estimate the class of each data point, quantification (or prevalence estimation) aims to estimate the

Evaluating Multi-Dimensional Generalization of Large Language Models in Temporal Extraction Tasks

arXiv:2610.02549v1 Announce Type: new Abstract: Time and event expression extraction are fundamental temporal reasoning tasks, but the problem remains difficult due to annotation ambiguity, domain sen

Event-guided Neural Video Compression

arXiv:2610.02265v1 Announce Type: cross Abstract: Neural video codecs derive motion and temporal contexts mainly from RGB frames, leaving room for cross-modal guidance from complementary temporal obse

Evolving Hybrid Quantum-Classical Architectures for Image Classification

arXiv:2610.03220v1 Announce Type: cross Abstract: Hybrid quantum classical neural networks integrate parameterized quantum circuits (PQCs) with established deep learning architectures, but their perfo

Expected Utility Regret Rule: Minimax and Bayes Optimal Portfolio Choice

arXiv:2610.02290v1 Announce Type: cross Abstract: This study considers the problem of portfolio choice, where we recommend a portfolio to an investor to maximize the expected utility of their wealth.

Explainable Molecular Structure Inference from GC--MS with Diffusion Models and LLM Reranking

arXiv:2610.03066v1 Announce Type: cross Abstract: GC--EI--MS is an important technique for analyzing volatile and semivolatile compounds in complex samples. However, conventional methods rely heavily

Exploring the Trade-Off Between Structured Pruning and Fault Tolerance in Deep Neural Networks for Space Applications

arXiv:2610.03117v1 Announce Type: new Abstract: Deep Neural Networks (DNNs) inherently exhibit a degree of robustness to bit-level faults due to their distributed representation of information. As a m

FASTDIAR: Frame-level speaker encoder for Streaming Diarization

arXiv:2610.02941v1 Announce Type: cross Abstract: Real-time conversational agents require speaker diarization that streams and runs on a CPU. Most systems apply an utterance-level speaker encoder to s

Feedforward Novel View Synthesis for Heterogeneous Cameras

arXiv:2610.03522v1 Announce Type: new Abstract: Feed-forward novel view synthesis has recently shown promising results from sparse posed images, but most existing methods assume that context and targe

FiberGeoText: A Vision-Language Model for Population- Level Organization of Superficial White Matter

arXiv:2610.02755v1 Announce Type: new Abstract: The superficial white matter (SWM), a critical brain region for cognition across the lifespan and brain disease, contains abundant short-range associati

FinDialogLens: Event Extraction over Multi-Party Dialogue for Missed-Trade Identification in Financial Chatrooms

arXiv:2610.02455v1 Announce Type: cross Abstract: Multi-party financial chatrooms are vital for sales-and-trading professionals, but their complexity makes manual recovery of missed trades infeasible:

Fragmentation is Efficiently Learnable by Quantum Neural Networks

arXiv:2512.00751v4 Announce Type: replace-cross Abstract: In certain classes of physical quantum systems, the exponentially large state space 'fragments' into many low-dimensional, dynamically disconn

From Behavior to Provenance: Attributing Tabular Foundation Models to Synthetic Pretraining Data

arXiv:2610.02347v1 Announce Type: new Abstract: Training-data attribution aims to identify which training examples shape model behavior, yet validating such claims is difficult because causal training

From Expression to Reaction: Role-aware Visual Transfer and Stimulus-guided Reasoning for Interlocutor Emotion Recognition

arXiv:2610.03016v1 Announce Type: cross Abstract: In this paper, we propose a Role-aware Stimulus-guided (RASG) framework for interlocutor emotion recognition, which predicts listener emotions from li

From Language Priors to Field Adaptation: Preference Learning for Traversability Estimation

arXiv:2610.02974v1 Announce Type: cross Abstract: Image-based traversability estimation is inherently dependent on the robot platform, deployment domain, and mission preferences, which limits the appl

From Mathematical to Executable Certificates for Machine Unlearning

arXiv:2610.02268v1 Announce Type: new Abstract: Machine unlearning is needed when data must be removed because of deletion requests, outdated records, or data-quality concerns, while retraining from s

From Patching to Pruning Visual Computation in Vision Language Models

arXiv:2610.03389v1 Announce Type: new Abstract: Vision language models (VLMs) incur substantial inference cost because every visual token is processed by the attention and MLP projections of every dec

Gated Slot Attention-2: Two-Sided Associative Memory Correction in Linear Attention

arXiv:2610.02816v1 Announce Type: new Abstract: Linear attention models have emerged as efficient alternatives to standard attention, but effectively managing their fixed-size recurrent memory remains

Generalizable single-cell perturbation response prediction using energy-guided flow matching

arXiv:2610.02232v1 Announce Type: cross Abstract: Predicting phenotypic and transcriptional responses to perturbations at single-cell resolution provides a powerful tool for probing biological systems

Generalization of Transformer-Based Neural Quantum States via In-Context Learning

arXiv:2610.03463v1 Announce Type: cross Abstract: Neural quantum states based on modern deep learning architectures have emerged as powerful representations for quantum many-body systems. In particula

Getting Your Guidance Weights Right in diffusion and flow-matching posterior sampling

arXiv:2610.03503v1 Announce Type: new Abstract: Training-free posterior sampling methods, also known as Plug-and-Play methods, leverage pretrained unconditional diffusion or flow-matching models to so

GRAFT: Growing Agglomerative Foundation Models via Continual Teacher Distillation

arXiv:2610.02597v1 Announce Type: new Abstract: Vision foundation models such as DINOv2, SigLIP2, and MASt3R develop complementary capabilities from different pretraining objectives, yet their knowled

Hamiltonian locality testing and certification do not achieve the Heisenberg limit

arXiv:2610.03205v1 Announce Type: cross Abstract: We establish lower bounds for Hamiltonian property testing with access to the time-evolution operator but not its inverse. Each experiment may query t

HARPO: Hallucination-Aware Reinforcement Learning for Faithful and Creative Language Generation

arXiv:2610.03063v1 Announce Type: new Abstract: Large Language Models (LLMs) are prone to generating hallucinated content, which compromises their reliability in knowledge-intensive tasks. To address

HexVIO: Towards All-Day Stereo-Inertial Tracking Through Commodity DSPs

arXiv:2610.03283v1 Announce Type: cross Abstract: The ability of a device to localize itself within its surroundings is a fundamental prerequisite for spatial computing. Visual-inertial odometry (VIO)

High-Dimensional Asymptotics of Differentially Private PCA

arXiv:2511.07270v4 Announce Type: replace-cross Abstract: In differential privacy, random noise is introduced to privatize summary statistics of a sensitive dataset before releasing them. The noise le

Hindsight-Guided Rationale Distillation for Rare Disease Diagnosis

arXiv:2610.03176v1 Announce Type: new Abstract: We study hindsight-guided distillation for rare disease diagnosis on ZebraMap: a 1.5B student is fine-tuned on chain-of-thought traces from a 8B teacher

Hold-Out Scoring for Efficient Gaussian DAG Learning

arXiv:2610.02785v1 Announce Type: cross Abstract: High-dimensional Gaussian DAG learning faces a statistical-computational gap: methods with sharp sample complexity rely on computationally expensive s

Hop-Decayed Influence: New Vulnerabilities of Structural Auxiliary Indexing in GraphRAG Pipelines with LLM

arXiv:2610.02373v1 Announce Type: cross Abstract: GraphRAG pipelines construct auxiliary structures during offline indexing--semantic summaries, hierarchical edges, and pre-computed scores--that deter

HyperFuse: Fast Self-Supervised Node Embeddings for Attributed Hypergraphs

arXiv:2610.03211v1 Announce Type: new Abstract: Self-supervised hypergraph representation learning can produce informative node embeddings, but existing methods often require deep encoders trained for

Hyperparameter selection for equation learning with biologically-informed neural networks

arXiv:2610.02954v1 Announce Type: new Abstract: Biologically-informed neural networks (BINNs) have emerged as a flexible subclass of physics-informed neural networks (PINNs) for learning terms in part

IGNITE Tokamak World Model Architecture

arXiv:2610.02515v1 Announce Type: cross Abstract: We introduce IGNITE, a generative world foundation model for fusion plasma behavior simulation trained in a self-supervised manner from over a decade

Information Limits of Low-Rank Approximation Certification

arXiv:2610.03321v1 Announce Type: cross Abstract: Low-rank approximation can require additional matrix--vector products to verify that its error meets a prescribed tolerance. We characterize this cert

Inner Momentum for Differentially Private Muon

arXiv:2610.02738v1 Announce Type: new Abstract: Differentially private training clips each per-example gradient before adding noise. This clipping is radial for each example, yet unequal clipping fact

Invariance of Clustering Operations in Causal Effect Identification

arXiv:2610.03101v1 Announce Type: cross Abstract: Clustering variables in causal graphs reduces the size of the graph and simplifies causal inference. However, arbitrary clustering can alter crucial c

Jumping up and down: Denoiser diffusion models for discrete ordinal data

arXiv:2610.02754v1 Announce Type: new Abstract: Diffusion models are highly developed in continuous spaces for image and video domains. Recently, major advances have been made for discrete diffusion m

Kernel Singular Value Decomposition with Extension to Multiple Data Sources

arXiv:2610.03216v1 Announce Type: new Abstract: Kernel Singular Value Decomposition (KSVD) learns a pair of singular vectors w.r.t. an asymmetric kernel matrix, which can be induced by two data source

KV^2: A Self-Refining KV Cache

arXiv:2610.03198v1 Announce Type: new Abstract: The memory footprint of the key-value (KV) cache constrains the practical use of long-context models, and it dominates cost when one prefilled context m

Label-Efficient Time Series Classification at Scale: A Dual-Stream OSSE-LSTM with Counterfactual Attribution

arXiv:2610.02704v1 Announce Type: new Abstract: Time series are produced continuously at enormous scale by industrial equipment, wearables, power grids, and clinical monitors, yet annotation remains m

Large Language Continuous Diffusion Models

arXiv:2610.02665v1 Announce Type: cross Abstract: Despite the success of discrete diffusion language models (dLMs) for fast parallel decoding, their non-smooth, high-dimensional space hinders trajecto

Large language models exhibit unreliable updating of clinical judgment as patient evidence evolves

arXiv:2610.02684v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly explored for clinical reasoning, but whether they appropriately revise judgments as patient evidence evolv

Learning Jazz Pianist Style with Cross-Attention Conditioning

arXiv:2610.02918v1 Announce Type: cross Abstract: Jazz pianists develop distinctive traits that experienced listeners can often identify within seconds, yet the features underlying this recognition re