Search: “research”

Algorithms for adaptive and heteroskedastic linear regression at the computational threshold

arXiv:2608.18402v1 Announce Type: cross Abstract: We study finite-sample linear regression in the presence of varied and unknown label noise, focusing on the heteroskedastic and adaptive linear regres

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Allocating Recurrent Compute in Looped Language Models

DGX agent

arXiv:2608.18230v1 Announce Type: new Abstract: Looped language models improve reasoning and knowledge manipulation by applying shared computation repeatedly. Existing systems usually repeat an entire

researcharxiv-cs-lg

20 Aug 2026

AlphaClifford: Efficient Clifford Synthesis and Transpilation with Model-based RL

arXiv:2608.18946v1 Announce Type: cross Abstract: Clifford circuits play a foundational role in quantum computing, particularly due to their importance in quantum error correction and fault-tolerant l

An Experimental Study of Downwash Effects on a Continuum Manipulator Integrated with a Multirotor UAV

arXiv:2608.18507v1 Announce Type: new Abstract: Continuum arm aerial manipulation systems leverage soft-manipulator compliance and dexterity for tasks in confined or hazardous environments, but propel

researcharxiv-cs-ro

Automated Computational Energy Minimization of ML Algorithms using Constrained Bayesian Optimization

arXiv:2407.05788v2 Announce Type: replace-cross Abstract: Bayesian optimization (BO) is an efficient framework for optimization of black-box objectives when function evaluations are costly and gradien

Backdoor Learning in Language Models and Vision-Language Models

arXiv:2608.18095v1 Announce Type: cross Abstract: Recent advances in deep learning have significantly enhanced the capabilities of Natural Language Processing (NLP) and Vision-Language Models (VLMs).

Backward Layout Search for Sequence-Constrained Robotic Assembly

arXiv:2608.18454v1 Announce Type: new Abstract: Robotic assembly layout planning must determine the assembly site and the initial pose of each part while ensuring collision-free execution of a prescri

researcharxiv-cs-ro

Banger paper on harness continual learning. (bookmark it) If you already are allowing your agents to rewrite their own prompts, skills, or m…

Banger paper on harness continual learning. (bookmark it) If you already are allowing your agents to rewrite their own prompts, skills, or memory files, this one is worth your time. (bookmark it) Cont

researchdair-ai--x

BERTilda: Explainable Topic Lifecycle Tracking with Split/Merge Detection via Similarity-and-Flow Temporal Graphs

arXiv:2608.18101v1 Announce Type: new Abstract: Longitudinal text streams exhibit topic birth and death, but also discrete structural reorganizations in which themes split into subtopics or merge into

Bound-Aware Per-Organ Recall Risk Control for Multi-Organ CT Segmentation under Clinical Domain Shift

arXiv:2608.18193v1 Announce Type: cross Abstract: Distribution-free risk control adds organ-specific recall guarantees to frozen segmentation. We calibrate per-organ thresholds for an AMOS-trained nnU

Bridge Graphical Models: Coupling, Projection, and Current-Preserving Dynamics for Generative Modeling

arXiv:2608.19144v1 Announce Type: new Abstract: Continuous-time generative models are often built from endpoint-conditioned bridges, but generation requires a different object: a non-anticipative Mark

Building real-time digital twin instances with Function+Data Flow: user evaluation and extension for iterative pipelines

arXiv:2608.18480v1 Announce Type: cross Abstract: Digital twins (DTs) increasingly leverage artificial intelligence (AI) and machine learning (ML) pipelines, both to build real-time DTs from high-fide

ChainWorld: Composing Long-Horizon Desktop Workloads from Atomic OSWorld Tasks

arXiv:2606.21654v2 Announce Type: replace Abstract: Computer use agents are evaluated almost exclusively on atomic desktop tasks, but realistic desktop work requires sustaining state across multiple o

ChiroEcho: extending automated bat vocalisation classification beyond the learned taxonomy

arXiv:2608.18191v1 Announce Type: new Abstract: Bats are key indicators of ecosystem health and are protected throughout Europe, making reliable population monitoring a conservation priority. Their cr

CoMVS-GS: Collaborative Multi-View Stereo and 3D Gaussian Splatting for Surface Reconstruction

arXiv:2608.18413v1 Announce Type: new Abstract: 3D Gaussian Splatting enables efficient novel view synthesis, but accurate mesh reconstruction remains difficult in weakly observed and occluded regions

Converting Expert Deliberation into Financial Signals Through A Context-Aware NLP Pipeline

arXiv:2608.18911v1 Announce Type: new Abstract: We introduce the CDSP (context-conditional deliberation signal pipeline), converting an investment committee's meeting transcripts into structured predi

Coordination on a Budget: Federated Active Learning with Few Labels

arXiv:2608.18634v1 Announce Type: new Abstract: Federated Active Learning (FAL) addresses the dual challenges of data privacy and label scarcity, where the absence of a global data view introduces add

Corrections of Zipf's and Heaps' Laws Derived from Hapax Rate Models

arXiv:2307.12896v5 Announce Type: replace Abstract: The article introduces corrections to Zipf's and Heaps' laws based on systematic models of the proportion of hapaxes, i.e., words that occur once. T

COSTA: A Cluster-Centric Paradigm for Annotation-Free Open-Set Semantic Segmentation of Aerial Point Clouds with Domain Shifts

arXiv:2608.18479v1 Announce Type: new Abstract: Semantic segmentation of aerial point cloud is trapped in a generalization crisis under distinct domain shifts. While test-time adaptation offers a priv

Counterfactual Contrastive Analysis

arXiv:2608.19032v1 Announce Type: cross Abstract: Visual Counterfactual Explanations (VCEs) aim to explain image classifiers by generating minimally edited and realistic versions of an input image tha

Cross-Modal MRI Ovary Segmentation in Endometriosis Using Unpaired TVUS Prototype Priors

arXiv:2608.18515v1 Announce Type: new Abstract: Transvaginal ultrasound (TVUS) and magnetic resonance imaging (MRI) provide complementary information for endometriosis image analysis, yet existing stu

DeGLIF for Label Noise Robust Node Classification using GNNs

arXiv:2506.00244v2 Announce Type: replace Abstract: Noisy labelled datasets are generally inexpensive compared to clean labelled datasets, and the same is true for graph data. In this paper, we propos

Denoising-Aware Inversion: Revealing Privacy Risks in Noise-Protected Text Embeddings

arXiv:2608.18610v1 Announce Type: cross Abstract: Dense text embeddings are widely used in data mining, retrieval, and downstream machine learning systems due to their compact and semantically rich re

DevGRU: Depth-guided Visual Navigation using a Collision-aware Recurrent Model

arXiv:2608.18470v1 Announce Type: new Abstract: Existing visual navigation models often aim to develop foundation models that can generalize robot navigation across diverse platforms. However, many of

researcharxiv-cs-ro

Different Facets of Verbalised Overconfidence: an Interpretability Study

arXiv:2608.18106v1 Announce Type: cross Abstract: Large language models tend to overconfidence, giving assertive answers when the evidence suggests hedging or abstention. Using controlled reasoning sc

Diffusion Models for High-Dimensional Clustered Data: Intrinsic-Dimension Adaptivity via Bayesian Classification

arXiv:2608.19067v1 Announce Type: cross Abstract: The empirical success of diffusion models in generative modelling has motivated theoretical work, including quantitative error bounds and qualitative

Model Releases

DigitalOcean Inference Router, Now Cache-Aware: Why the Cheapest Model Isn't Always the Best Deal

model-releasesdigitalocean

Coinbase CEO Brian Armstrong recently posed the question every company scaling AI is asking: how do you keep spend flat while token usage grows exponentially? This isn’t hypothetical. It’s confronting

Do Large Language Models Hallucinate Electric Fata Morganas?

arXiv:2608.18816v1 Announce Type: cross Abstract: AI hallucinations - that is, outputs which are made up, cannot be verified, or contradict the source material - are generally regarded as an engineeri

Does Mapping Non-Maximal Probabilities to GMM Components Matter for S-JEPA Encoder Representations?

arXiv:2608.19084v1 Announce Type: new Abstract: S-JEPA uses soft Gaussian mixture model (GMM) posteriors instead of hard cluster labels to preserve uncertainty. It remains unclear whether the probabil

Efficient INT8 Inference of Small NLP Models on Server CPUs with PyTorch Native Stack

arXiv:2608.18182v1 Announce Type: new Abstract: Small NLP models, especially BERT-family encoders, remain important in industrial workloads such as classification, ranking, and retrieval even in the e

Enhancing Distance-Based Graph Autoencoders with Structural Penalties for Dynamic Graph Embedding

arXiv:2608.18762v1 Announce Type: new Abstract: Graph autoencoders (GAEs) are widely used for learning representations of dynamic graphs. However, their optimisation objectives typically do not take s

Evaluating and Explaining Prompt Sensitivity of LLMs Using Interactions

arXiv:2608.18539v1 Announce Type: cross Abstract: The remarkable capabilities of large language models (LLMs) are often undermined by their instability. Even subtle and semantically irrelevant changes

Evaluation of Image Matching Methods for Visual Odometry on UAVs

arXiv:2608.18624v1 Announce Type: new Abstract: Unmanned aerial vehicles (UAVs) are becoming a powerful tool for many environmental monitoring and transport applications. Yet, their reliance on Global

Fair Multi-View Determinantal Coresets via Adaptive NEPv

arXiv:2608.18181v1 Announce Type: cross Abstract: Selecting a small, diverse subset from a large candidate pool often means balancing several incompatible notions of diversity. In trademark curation,

Forgetting, plasticity, and co-observation: a third facet of continual learning

arXiv:2608.18803v1 Announce Type: cross Abstract: Efficient continual learning remains a fundamental challenge for deep neural networks. While catastrophic forgetting and loss of plasticity are widely

Formal Verification of Romanov's Triplet Logic: A Verified Filter for Sliding-window 3-CNF with Application to Structured Formulas

arXiv:2608.18445v1 Announce Type: cross Abstract: We present the first mechanised formalisation of Romanov's Triplet Logic (TLS) in the Rocq proof assistant. TLS is a triplet-based combinatorial frame

Foundations of Diffusion Models in General State Spaces: A Self-Contained Introduction

arXiv:2512.05092v2 Announce Type: replace-cross Abstract: Although diffusion models now occupy a central place in generative modeling, introductory treatments commonly assume Euclidean data and seldom

FRAGMENT: Factorized Graph Representations for Document Generation and Editing via Entity-Aware Transformations

arXiv:2608.18679v1 Announce Type: new Abstract: Structured documents such as invoices, forms, reports, and scientific articles derive meaning from the interplay between spatial layout, textual content

Fuzzy Accuracy Compensates for Label Subjectivity in Classification of Skin Tone Using Wearable Photoplethysmography Signals

arXiv:2608.18969v1 Announce Type: new Abstract: We consider the problem of classification of skin tone using photoplethysmography (PPG) signals with labels of the ordinal six-class Fitzpatrick skin to

GCNO: Gramian Chebyshev Neural Operator for Physics-Based Compression of Wireless Channels

arXiv:2608.18522v1 Announce Type: cross Abstract: Large antenna arrays allow wireless systems to serve more users and achieve higher data rates, but they also make channel feedback expensive: the rece

GEAR: Generative Expansion and Real Anchoring for Two-Stage Distillation of Tabular Foundation Models

arXiv:2608.18849v1 Announce Type: new Abstract: Tabular foundation models (TFMs) achieve strong performance through in-context learning, but context-dependent inference imposes substantial latency and

Generalizable AI-Generated Image Detection Based on Fractal Self-Similarity in the Spectrum

arXiv:2503.08484v2 Announce Type: replace Abstract: With the rapid development of image synthesis techniques, AI-generated images have become increasingly realistic, which heightens the potential risk

Geometric Iterative Retrieval for Neural Audio Codec Resynthesis

arXiv:2608.19141v1 Announce Type: cross Abstract: Neural audio codecs based on Residual Vector Quantization (RVQ) have become the dominant discrete representation for token-based general audio generat

Gradient Mirage: Trainable yet Label-Unidentifiable Gradients in Large Language Model Split Learning

arXiv:2608.18767v1 Announce Type: new Abstract: Gradient matching attacks (GMAs) in LLM split learning (SL) rely on a critical yet underexplored assumption: the gradient exposed at the split interface

Graphical Design of Interpretable Architectures

arXiv:2608.18936v1 Announce Type: cross Abstract: Designing, implementing, and comparing interpretable architectures requires a formal language to represent them. The most common representations fall

Hallucination Detection in Large Language Models Using Diversion Decoding

arXiv:2607.10476v2 Announce Type: replace Abstract: Large language models (LLMs) have emerged as a powerful tool for retrieving knowledge through seamless, human-like interactions. Despite their advan

How Do VLMs Fail? Vision-Operation Misalignment in Compositional VQA

arXiv:2607.16094v2 Announce Type: replace Abstract: Compositional visual question answering requires Vision-Language Models (VLMs) to execute multiple reasoning operations like object selection, spati

Identifying Implicit Premises for Logical Reconstruction of Argument Graphs

arXiv:2608.18821v1 Announce Type: cross Abstract: The logical reconstruction of argument graphs from natural language text is challenging because of the prevalence of enthymemes (i.e., arguments with