Search: “models”

Beyond Accuracy: Community Perspectives on Machine Translation

model-releasesarxiv-cs-cl

arXiv:2606.09655v2 Announce Type: replace Abstract: Despite remarkable progress in machine translation (MT), non-AI communities have raised growing concerns about MT systems, suggesting a noticeable g

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Beyond Endpoint Scores: Time- and Capacity-Conditioned Evaluation of Continual Knowledge Updating

DGX agent

arXiv:2609.03900v1 Announce Type: new Abstract: Continual knowledge-updating methods are often declared superior from one final checkpoint and one conventional adapter rank. We show that this can be i

model-releasesarxiv-cs-lg

4 Sept 2026

Beyond Majority Vote: Multi-Perspective Adjudication for Medical Hallucination Detection

model-releasesarxiv-cs-cl

arXiv:2609.03953v1 Announce Type: new Abstract: Understanding the frequency of factual errors in chatbot-generated text and evaluating systems that detect these errors is critical for determining chat

Beyond Small Patches: Black-Box Detection and Purification of Diverse Backdoor Triggers

arXiv:2609.03139v1 Announce Type: new Abstract: Deep neural networks (DNNs) are increasingly deployed in real-world vision systems, yet their predictions can be covertly manipulated by backdoor attack

applicationsarxiv-cs-cv

Beyond Straightness: Non-Crossing Flow Matching via Quantile AlignTree Coupling

arXiv:2609.03443v1 Announce Type: new Abstract: The performance of Flow Matching largely depends on the quality of the coupling between the source and target distributions. However, independent coupli

CoFiE: Coarse-to-Fine Evidence Selection for Efficient Streaming Video Understanding

arXiv:2609.03675v1 Announce Type: new Abstract: Streaming video understanding requires Vision Language Models (VLLMs) to process growing video streams and answer user questions under tight latency con

Compile by Training: Turning Natural-Language Specifications into Local Neural Functions

arXiv:2609.04199v1 Announce Type: cross Abstract: Many recurring text functions are easy to describe but difficult to implement with rules, while calling a large remote model for every input introduce

applicationsarxiv-cs-ai

Cooperative Multi-Task Semantic Communication for Joint Classification and Regression Tasks

arXiv:2609.03977v1 Announce Type: cross Abstract: Multi-Task semantic communication (SemCom) prioritizes simultaneous execution of multiple tasks over bit-accurate reconstruction in future intelligent

Coupled Tensor-Tensor Completion Method with Applications in Drug Repurposing

arXiv:2609.03190v1 Announce Type: cross Abstract: Many biomedical challenges can be posed as tensor completion problems where the observed entries of a multidimensional array (a tensor) are used to im

Decoupled Analysis-Judging: An Automated Creativity Evaluator Using LLMs in Complex Multi-step Creativity Tasks

arXiv:2609.03432v1 Announce Type: new Abstract: Automated evaluation of creativity tasks remains challenging for LLM-as-a-Judge, as LLM is susceptible to biases such as verbosity bias and leniency bia

safetyarxiv-cs-cl

Distilling deep optical flow stereo methods to retrieve dense three-dimensional wind fields

arXiv:2609.03100v1 Announce Type: new Abstract: Geostationary atmospheric motion vectors (AMVs) provide the dense horizontal wind vectors (u,v) and heights ingested into data assimilation systems. Tra

researcharxiv-cs-lg

Do GUI Agents Know When Not to Act? Enabling Conflict-Aware Termination for Multimodal GUI Agents

model-releasesarxiv-cs-ai

arXiv:2609.03438v1 Announce Type: new Abstract: Graphical user interface (GUI) agents are increasingly used to execute natural-language instructions on user interfaces, yet real users may issue infeas

Efficient Constant Optimization for Symbolic Regression with GPU-Accelerated Tree-Based Genetic Programming

arXiv:2609.03352v1 Announce Type: cross Abstract: Constant optimization refines the numerical coefficients of candidate expressions in tree-based genetic programming for symbolic regression. But its p

Entropy-Generated Attention Beyond Softmax and Entmax: Kaniadakis and Reciprocal-Symmetric Abe Operators

arXiv:2602.08216v3 Announce Type: replace Abstract: We derive two attention operators from generalized statistical entropies. Kaniadakis entropy yields an exact full-support normalization whose weight

Equilibria for Networks of Linear Translational Springs

model-releasesarxiv-cs-ro

arXiv:2609.03143v1 Announce Type: cross Abstract: We use tools from nonlinear algebra to study the equilibria of small linear translational spring networks. Specifically we use the techniques of homot

Evaluating GNNs for Success Prediction in Artist Collaboration Networks

arXiv:2609.02920v1 Announce Type: cross Abstract: As the music industry becomes an increasingly collaborative effort, understanding the underlying structures of the artist network has become a focal p

researcharxiv-cs-lg

FlashRender: Few-Step Generative Rendering via Camera-Controlled Video MeanFlow

arXiv:2609.03563v1 Announce Type: new Abstract: We present FlashRender, a few-step generative rendering framework that retakes a source video along a target camera trajectory in seconds. We identify s

safetyarxiv-cs-cv

FlowBalance: Verifier-Grounded Self-Improvement from On-Policy Reasoning Experience

arXiv:2609.03241v1 Announce Type: cross Abstract: A reasoning model can improve from its own on-policy experience, but this inner loop is fragile: terminal verifiers provide reliable yet sparse superv

safetyarxiv-cs-ai

From Euclidean to Graph-Structured Data: A Survey of Collaborative Learning

arXiv:2609.02984v1 Announce Type: new Abstract: The conventional approach to machine learning, that is, collecting data, training models, and performing inference in a single location, faces fundament

applicationsarxiv-cs-lg

Tutorials

From Nowcasting to Forecasting: Adapting a Reanalysis-Trained

arXiv:2609.03763v1 Announce Type: new Abstract: Accurate cloud-cover forecasts are important for temperature prediction, radiation forecasting, and solar-power operations. Short-range forecasting meth

tutorialsarxiv-cs-lg

Generative Nested Sampling of Atomistic Thermodynamic Landscapes

arXiv:2609.03193v1 Announce Type: cross Abstract: Nested sampling (NS) resolves the thermodynamics of an atomistic system from a single simulation, but its practical reach is limited by the Markov-cha

Grassmann--Plucker Parametrization of Convolutional Filter Subspaces: Regularity and Closed Embeddings

arXiv:2609.03361v1 Announce Type: cross Abstract: We propose a geometric parametrization of the filters in a single convolutional layer: the parameter is no longer an ordered family of filter vectors,

KernelFoundry: Hardware-aware evolutionary GPU kernel optimization

arXiv:2603.12440v2 Announce Type: replace-cross Abstract: GPU kernel optimization challenges LLMs beyond standard coding tasks, as it requires an understanding of hardware architecture, parallel compu

LeanGRPO: Eliminating Redundant Recomputation in Diffusion RL

arXiv:2609.03528v1 Announce Type: cross Abstract: Diffusion reinforcement learning (RL) has recently achieved significant success in post-training image and video generative models. However, most diff

safetyarxiv-cs-ai

Learning from Scarce Labels: Multi-View Echocardiography for Ejection Fraction Prediction

arXiv:2609.02969v1 Announce Type: cross Abstract: We present, to the best of our knowledge, the first publicly available resource for predicting left ventricular ejection fraction (EF) from parasterna

M3T: Discrete Multi-Modal Motion Tokens for Sign Language Production

arXiv:2603.23617v2 Announce Type: replace Abstract: Sign language production requires more than hand motion generation. Non-manual features, including mouthings, eyebrow raises, gaze, and head movemen

applicationsarxiv-cs-cv

MasterControl Seventeen Every Time

arXiv:2609.03209v1 Announce Type: new Abstract: We study a governed approach to enterprise analytics: a language model interprets the question, while deterministic policy selects and runs a pre-approv

safetyarxiv-cs-ai

Observation-Conditioned Latent Energy Priors for Sparse Implicit Neural Shape Completion

arXiv:2609.03694v1 Announce Type: new Abstract: Implicit neural representations (INRs) can model continuous 3D shapes with a shared coordinate decoder and per-instance latent codes. At test time, auto

OctWorld: Long-Range World-Consistent Video Generation with Octree-Based 3D Mapping

arXiv:2609.03919v1 Announce Type: new Abstract: We present OctWorld, a video diffusion framework with persistent 3D memory for generating explorable, world-consistent, and high-fidelity visual scenes.

Agents

ORMOT: A Dataset and Framework for Omnidirectional Referring Multi-Object Tracking

arXiv:2603.05384v2 Announce Type: replace Abstract: Omnidirectional cameras provide 360{eg} spatial coverage, making them increasingly valuable in applications such as autonomous driving and video sur

agentsarxiv-cs-cv

Parameterised graph theory for tensor networks: entanglement rerouting, structural simplification, and agnostic tomography

arXiv:2609.04165v1 Announce Type: cross Abstract: Parameterised graph theory studies how the complexity of graph-theoretic problems depends on structural parameters of the input graph. This perspectiv

ProAct: Harnessing Streaming Motion Generation and Agentic Reasoning for Real-Time Embodied Social Interaction

model-releasesarxiv-cs-cv

arXiv:2602.14048v2 Announce Type: replace-cross Abstract: Real-time embodied social interaction places two equally demanding requirements on an agent: continuously generating fluent multimodal interac

Local Ai

Pushing the (Decision) Boundaries: Dynamically Calibrating Differentially Private Noise to Explainability in Federated Learning

arXiv:2609.03851v1 Announce Type: new Abstract: Federated Learning (FL) with Differential Privacy (DP) is increasingly adopted to preserve data confidentiality in distributed machine learning. However

local-aiarxiv-cs-lg

R^{2}Adapter: A Routing and Rewriting Adapter for Efficient Hybrid RAG

arXiv:2609.02894v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has become a prevailing paradigm for enhancing Large Language Models (LLMs) with non-parametric knowledge. Vanilla

researcharxiv-cs-cl

Reflect-SQL: A Self-Reflection Based Framework for Text-to-SQL

model-releasesarxiv-cs-ai

arXiv:2609.02944v1 Announce Type: cross Abstract: Democratizing data access through natural language is a crucial goal for modern enterprises, but the practical adoption of Text-to-SQL is critically h

Residual Optimal Transport-Based Experts Collaboration Towards Modality-Aware Infrared-Visible Object Detection

model-releasesarxiv-cs-cv

arXiv:2609.03516v1 Announce Type: new Abstract: Infrared-visible object detection (IVOD) integrates complementary evidence from visible and infrared sensors for reliable perception in challenging scen

Restricted Eigenvalues Beyond Gaussian Width: Threshold Occupancy under Heavy Tails

arXiv:2609.03504v1 Announce Type: new Abstract: Restricted eigenvalue (RE) bounds govern stable recovery by norm-regularized estimators. For isotropic sub-Gaussian measurements, the benchmark sample s

Robust PAC Learning of Concurrent Stochastic Games

arXiv:2609.04189v1 Announce Type: new Abstract: We introduce the first Probably Approximately Correct (PAC) learning framework for general-sum concurrent stochastic games (CSGs) with transition uncert

Stabilizing Camera-Controlled Novel View Synthesis at Inference Time

arXiv:2609.03639v1 Announce Type: new Abstract: Training-free, camera-controlled novel view synthesis from a single image using pre-trained video diffusion models often becomes unstable under large ca

STARS-GS: Structure-Aware Regularized Gaussian Splatting for Large-Scale Aerial Surface Reconstruction

arXiv:2609.03447v1 Announce Type: new Abstract: Large-scale 3D surface reconstruction from aerial imagery is fundamental to geospatial mapping and urban modeling. Recent advances in 3D Gaussian Splatt

Tutorials

Statistical Feature Augmentation for Anomaly Detection in Dynamic Graphs

arXiv:2609.02965v1 Announce Type: cross Abstract: Dynamic networks are being applied in many domains, from social media to logistics systems, each with their own set of special characteristics. A mode

tutorialsarxiv-cs-lg

Test-time adaptation for speech enhancement with an autoregressive speech prior

arXiv:2609.03622v1 Announce Type: cross Abstract: Test-time adaptation (TTA) offers a promising direction for improving speech enhancement models under mismatched acoustic conditions, without requirin

researcharxiv-cs-ai

The Blind Spot in 2D Infants' Pose Estimation:Robust Learning from Noisy Annotations

arXiv:2609.04009v1 Announce Type: cross Abstract: Noisy annotations pose a significant challenge for supervised deep learning, as neural networks rely on large-scale, high-quality labeled data whose c

researcharxiv-cs-ai

Tree-Structured Vector Quantization For Efficient And Progressive Image Compression

arXiv:2609.03641v1 Announce Type: new Abstract: Vector-quantization based image compression has achieved strong rate--distortion performance, yet most of them still produce a separate compressed repre

Verify Before You Distill: Prompt-Level Teacher Gating for On-Policy Distillation

model-releasesarxiv-cs-ai

arXiv:2609.02998v1 Announce Type: cross Abstract: On-policy distillation (OPD) accelerates post-training by providing dense token-level supervision from a frozen teacher on the student's own rollouts.

Local Ai

Why Gated DeltaNet Survives 4-Bit Quantization: NVFP4 W4A4 for the Recurrent Half of a Hybrid 27B LLM

arXiv:2609.04098v1 Announce Type: new Abstract: Hybrid LLMs pair softmax attention with linear-attention layers such as Gated DeltaNet (GDN), whose recurrent state summarizes the context in fixed size

local-aiarxiv-cs-ai

A Physics-Consistent Benchmark for Contact-Rich Human-Robot Interaction in Assistive Care

model-releasesarxiv-cs-ro

arXiv:2609.02402v1 Announce Type: new Abstract: Conventional task-level evaluation asks whether a robot policy completes a specified action, but can miss failures that emerge only during physical huma

3 Sept 2026

Agents

A Survey on Self-Improving Test-Time Intelligence: Feedback-Driven Adapting, Learning, and Scaling at Inference