research

EnComp: Lightweight Encoder-Only Context Compression for Retrieval-Augmented Question Answering

arXiv:2603.09222v2 Announce Type: replace Abstract: Efficient context compression is critical for retrieval-augmented question answering in resource-constrained settings, where long retrieved contexts

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Enhancing Multiclass Malware Classification in Resource-Constrained Environments

DGX agent

arXiv:2609.27950v1 Announce Type: cross Abstract: The emergence of multi-class malware attacks such as ransomware, spyware, trojans, etc., presents an increasing and serious threat to cybersecurity, p

researcharxiv-cs-lg

24 Sept 2026

Enhancing Small Language Models for Power Outage Report Generation via Minimum Risk Training

arXiv:2609.27197v1 Announce Type: new Abstract: Minimum Risk Training (MRT) enables neural machine translation models to directly optimize sequence-level evaluation metrics instead of relying only on

Evaluating ADC-only deep learning pipelines for breast cancer detection and segmentation using standalone diffusion-weighted MRI

arXiv:2609.27815v1 Announce Type: cross Abstract: Dynamic contrast-enhanced (DCE) imaging is the gold standard technique for the detection and characterization of breast cancer using magnetic resonanc

Evaluation of pre-trained models for pedagogical assessment of novel AI-assisted educational questions

arXiv:2609.27749v1 Announce Type: new Abstract: The surge in AI-assisted generation of educational materials has outpaced our capacity to validate their pedagogical quality. Automated evaluation using

EvoAudio: Recursive Self-Improvement for Audio Understanding

arXiv:2609.27389v1 Announce Type: cross Abstract: Audio language models understand what is said far better than how it sounds. Closing this gap takes more than data. Detailed acoustic annotation is co

Evolving Inspectable O-RAN Slicing xApps with LLMs

arXiv:2609.27337v1 Announce Type: cross Abstract: Open RAN (O-RAN) slicing xApps must adapt resource allocations to changing channel conditions and traffic demands while meeting service-level agreemen

Exact Feedback Is Not Control: Evaluating Text-based Closed-Loop Revision in LLMs

arXiv:2609.28150v1 Announce Type: new Abstract: Closed-loop revision is increasingly used in large language model (LLM) applications, but failures may reflect incomplete feedback or ineffective respon

researcharxiv-cs-cl

Experts Rise Where LLMs Disagree: Using Cross-Model Disagreement to Target Expert Effort in LLM Codebook Revision for Large-Scale Annotation

arXiv:2609.26926v1 Announce Type: cross Abstract: Large-scale text annotation brings expert insight to millions of documents, often through a codebook that AI annotators follow. Developing a robust co

FastManly: An EM-Gradient Algorithm for Manly Mixture Models

arXiv:2410.00848v2 Announce Type: replace-cross Abstract: A faster implementation of mixtures of Manly transformations is proposed. This method, called FastManly, uses Newton's method for optimization

Feed the Panel Dimensions, Not Verdicts: Rubric-Decomposed Fusion of Vision-Language Aesthetic Judges

arXiv:2609.27110v1 Announce Type: cross Abstract: Vision-language models (VLMs) are deployed as zero-shot judges of image aesthetics, and panels of several models are recommended, on thin evidence, as

researcharxiv-cs-cl

Field-of-View Extension in Dental Cone-Beam CT via Implicit Neural Representations and Diffusion Model-Based Refinement

arXiv:2609.28110v1 Announce Type: cross Abstract: Dental cone-beam computed tomography (CBCT) systems often employ detector configurations that provide a truncated field of view (FOV) that only captur

Fine-Tune, Then Rectify

arXiv:2511.19486v3 Announce Type: replace-cross Abstract: Driven by recent advances in artificial intelligence, a growing literature has demonstrated the potential of using large language models (LLMs

Fine Wrist Control as a Marker of Surgical Teleoperation Expertise

arXiv:2609.27160v1 Announce Type: new Abstract: Unlike most intensely physical pursuits, surgical robotic teleoperation training focuses primarily on task outcomes rather than surgeon body posture or

Forecast Workflow Bench: Evaluating Language-Model Decisions with Budgeted Forecast Tools

arXiv:2609.27385v1 Announce Type: cross Abstract: Time-series foundation models (TSFMs) provide forecasts for operational decisions, but accuracy alone does not determine their value. Evaluating agent

Forget who you Forgot: Speaker Unlearning to Prevent Re-Identification in Zero-Shot Text-to-Speech

arXiv:2609.27399v1 Announce Type: cross Abstract: Recent zero-shot text-to-speech (ZS-TTS) systems can reproduce a speaker's voice with high fidelity from only a few seconds of reference speech, raisi

From ECG Signals to Representative-Morphology Heatmaps for Biometric Recognition

arXiv:2609.28183v1 Announce Type: new Abstract: Electrocardiography (ECG) contains subject-specific morphology that supports biometric recognition, yet image-based performance depends on how the wavef

Frozen Flows Forget: Diagnosing and Restoring Lost Motion in a Latent-flow World Model

arXiv:2609.28414v1 Announce Type: cross Abstract: Latent world models that integrate a flow in a frozen self supervised latent space train stably and cheaply, yet silently lose the property manipulati

GaussPDE: Graph-Based Partial Differential Equation-Driven Rendering for 3D Gaussian Splatting

arXiv:2609.27264v1 Announce Type: new Abstract: We present GaussPDE, a framework that injects physically structured partial differential equation (PDE) dynamics into pretrained 3D Gaussian scenes with

Generalizable Robotic Insertion with World Models

arXiv:2609.28258v1 Announce Type: cross Abstract: Robotic assembly in high-mixture settings requires adaptable systems that can handle diverse parts, yet current approaches typically rely on policies

Geometry-anchored PET-aware multimodal pseudo-CT synthesis for whole-body attenuation correction: the BIC-MAC Challenge

arXiv:2609.27848v1 Announce Type: new Abstract: The BIC-MAC challenge targets whole-body pseudo-CT synthesis from NAC-PET, Dixon MRI, and a 2D topogram for CT-less PET attenuation correction. We propo

Geospatial embeddings detect old-growth forests but buffered spatial validation narrows their advantage over Sentinel features

arXiv:2609.28194v1 Announce Type: cross Abstract: Old-growth forests develop over centuries under minimal anthropogenic disturbance, producing structurally complex and biodiverse stands. In Europe, pr

GLOW: Global Illumination-Aware Inverse Rendering of Indoor Scenes Captured with Dynamic Co-Located Light & Camera

arXiv:2511.22857v2 Announce Type: replace Abstract: Inverse rendering of indoor scenes remains challenging due to the ambiguity between reflectance and lighting, exacerbated by inter-reflections among

Godel's and Scott's Variants of the Ontological Argument in Lean 4

arXiv:2609.26806v1 Announce Type: cross Abstract: This paper presents a complete, structure-preserving port to Lean 4 of the Isabelle/HOL dataset accompanying Benzmuller and Scott's study of Godel's m

Graph Learning with Spectral Connectivity Priors for Scarce Data

arXiv:2609.27278v1 Announce Type: new Abstract: Learning a sparse graph from scarce data is practically important but challenging. Motivated by the desirable combination of local sparsity and strong g

HARN: Hierarchical Associative Resonance Network for Event-Driven Multi-Timeframe Forecasting

arXiv:2609.26822v1 Announce Type: new Abstract: Financial time series evolve across multiple temporal resolutions, challenging forecasting systems to incorporate newly available information without re

Hidden not Deleted: How Networks Suppress Entangled Features

arXiv:2609.27593v1 Announce Type: cross Abstract: Concept erasure methods that operate via linear projection assume that features occupy separable subspaces. We show this assumption fails under dense

HINT-Blimp: Human INTent Inference from Multimodal Cues for Robotic Blimps

arXiv:2609.27154v1 Announce Type: new Abstract: In human-robot interaction, traditional interfaces such as joysticks and handheld tablets introduce latency into navigation tasks and require the operat

Honest and Reliable Evaluation and Expert Equivalence Testing of Automated Neonatal Seizure Detection

arXiv:2508.04899v3 Announce Type: replace Abstract: Reliable evaluation of machine learning models for neonatal seizure detection is critical for clinical adoption. Current practices often rely on inc

How Children Design and Reason about Trustworthy AI Chatbots

arXiv:2609.25244v2 Announce Type: replace-cross Abstract: Children increasingly interact with AI chatbots, making trust calibration essential to AI literacy. Prior research has examined children's tru

How Sensitive Are LLM Leaderboard Claims to Hidden Model Selection?

arXiv:2609.28177v1 Announce Type: cross Abstract: LLM leaderboard gains can reflect selection among privately evaluated model variants, yet neither the number of variants nor their dependence is publi

Hybrid Gaussians for Robust Open-Vocabulary 3D Segmentation with Multi-View Object Association and Boundary Refinement

arXiv:2609.27462v1 Announce Type: new Abstract: Open-vocabulary 3D segmentation localizes objects from free-form text queries, but remains challenging in real image sequences: incomplete or noisy 2D s

HYDRO: Towards Non-Reversible Face De-Identification Using a High-Fidelity Hybrid Diffusion and Target-Oriented Approach

arXiv:2609.27011v1 Announce Type: new Abstract: Target-oriented face de-identification models aim to anonymize the identity of a target individual across different images or video frames, such that th

hyperbolix: Hyperbolic Deep Learning in JAX

arXiv:2609.28248v1 Announce Type: new Abstract: We present hyperbolix, an open-source library for hyperbolic deep learning in JAX, built on Flax NNX. To our knowledge, it is the first comprehensive, g

Image Denoising Using Lower Semi-Frames

arXiv:2609.27893v1 Announce Type: cross Abstract: A blind image denoising framework based on an infinite directional lower semi-frame (DLSF) is proposed for additive white Gaussian noise. The model em

Impressive paper from Salesforce. It discusses the importance of good verifiers for RL environments. Only 35.8% of the environments in the c…

Impressive paper from Salesforce. It discusses the importance of good verifiers for RL environments. Only 35.8% of the environments in the cleanest public RL collection for terminal agents passed Sale

researchdair-ai--x

Information Capacity of Generative Video Compression: Quantifying the Rate-Compute Exchange at Identical Quality

arXiv:2609.27493v1 Announce Type: new Abstract: Under the AI Flow framework, communication networks distribute intelligence across devices, edge servers, and clouds, and computation at the receiver be

Integrated Multivariate Segmentation Tree for Heterogeneous Credit Data Analysis in Small- and Medium-Sized Enterprises

arXiv:2509.00550v3 Announce Type: replace-cross Abstract: Traditional decision tree models, which rely exclusively on numerical variables, often face challenges in handling high-dimensional data and a

Kairos: Grounded Forecasting of Presence and Directional Flow in 4D Scene Graphs

arXiv:2609.27467v1 Announce Type: cross Abstract: Long-term autonomy in human-populated environments requires anticipating whether and how people will move at times a robot has not yet observed. Exist

Large Knowledge Model: From Papers to a Scientific Reasoning Landscape

arXiv:2609.27297v1 Announce Type: new Abstract: Accumulated scientific knowledge advances inquiry when prior findings help researchers choose new questions, design investigations, and interpret result

Large-Scale Geometric Map-Based Localization of UAVs in GNSS-Denied Urban Environments

arXiv:2609.28225v1 Announce Type: new Abstract: Unmanned aerial vehicles (UAVs) operating in GNSS-denied urban environments require alternative methods for position estimation. Existing approaches bas

Laser-Tracker-Assisted Camera-to-Robot Calibration for Mobile Robots

arXiv:2609.27006v1 Announce Type: cross Abstract: We present a laser-tracker-assisted hand-eye calibration method for camera-equipped mobile robots. The method combines laser-tracker-based 3D metrolog

Learning Collective Dynamics with Differentiable Gaussian Representations

arXiv:2609.28405v1 Announce Type: new Abstract: Collective responses depend on individual differences, contact opportunities, and accumulated experience. Learning their dynamics from aggregate counts

Learning Dissipative Dynamics with Dissipativity-by-Construction Discrete-Time Neural Networks

arXiv:2609.27188v1 Announce Type: new Abstract: Dissipativity is a fundamental system-theoretic property closely related to stability, passivity, and input--output stability, and is particularly impor

Learning to Detect Symbolic Failure: Machine Learning and the Limits of Black-Scholes

arXiv:2609.27764v1 Announce Type: new Abstract: We treat options pricing as a representation problem: can machine learning detect systematic deviations from Black-Scholes using 2.6M real option contra

Lessons learned from deploying imaging AI with the open PACS-AI platform

arXiv:2609.26981v1 Announce Type: new Abstract: We describe deploying imaging AI at six hospitals through PACS-AI, an open self-hosted platform. The binding constraint is not model accuracy but infras

Linear RNN Scaling Laws: When Longer Sequences Beat More Sequences

arXiv:2609.27964v1 Announce Type: new Abstract: Empirical scaling laws for autoregressive language models relate prediction loss to model size, data size, and optimization compute, but their theoretic

Local Geometric Mixing via Dobrushin Contraction with Applications to Diffusion Path Monte Carlo and the Proximal Sampler

arXiv:2609.28338v1 Announce Type: cross Abstract: Local geometric mixing localizes geometric mixing by requiring geometric convergence to equilibrium in total variation only over finitely many transit