All entries

Evaluating Language Models in Realistic Conversational Contexts

model-releasesarxiv-cs-cl

arXiv:2608.26131v1 Announce Type: new Abstract: As Large Language Models (LLMs) are increasingly deployed to serve open-ended, multi-turn interactions, evaluating conversational quality at human scale

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Evaluator-Dependent Patient-Adaptive ECG Lead-Channel Allocation

DGX agent

arXiv:2608.26827v1 Announce Type: new Abstract: Patient-conditioned acquisition policies for ECG lead-channel selection can outperform population-wide fixed protocols by tailoring the channel budget t

safetyarxiv-cs-cv

28 Aug 2026

Explainable Artificial Intelligence for Customer Churn Prediction in Telecommunications: A Framework for CRM Integration

arXiv:2608.26151v1 Announce Type: new Abstract: Subscriber attrition is a costly, persistent challenge for telecommunications providers, with monthly churn of roughly 1.9% in mature markets eroding bi

Exploring the Role of LLMs in HPC Programming: A Survey

arXiv:2608.26110v1 Announce Type: cross Abstract: Large Language Models (LLMs) are emerging as promising assistants in High-Performance Computing (HPC), where programming remains complex and expertise

applicationsarxiv-cs-ai

Local Ai

Fairness Invariants: A Relational Approach to Explaining and Mitigating Fairness Bugs

arXiv:2608.26209v1 Announce Type: cross Abstract: Data-driven software systems are increasingly deployed in high-stakes socio-economic domains, from criminal justice to financial lending. However, the

local-aiarxiv-cs-ai

FaithSieve: Fine-Grained Evaluation of Math Proofs with Faithful Formal Evidence

arXiv:2608.26310v1 Announce Type: new Abstract: Large language models can now generate complex, multi-step mathematical proofs, but reliably determining their correctness and localizing early logical

FAN-LoRA: A Fourier-Adaptive Nonlinear Low-Rank Adaptor for Medical Foundation Model Domain Adaptation

model-releasesarxiv-cs-cv

arXiv:2608.26531v1 Announce Type: new Abstract: The advent of vision foundation models, notably the Segment Anything Model (SAM), has catalyzed significant advancements in natural image segmentation.

FaulT-Bench: Towards Benchmarking Network Troubleshooting LLM Agents under Unreliable User Tickets

arXiv:2608.27021v1 Announce Type: cross Abstract: LLM-based agents are increasingly proposed for network fault diagnosis, but existing benchmarks evaluate them only on accurate tickets and always assu

FaultLens: Learning Compact Behavioral Test Suites for Generated Operational Programs

arXiv:2608.26746v1 Announce Type: cross Abstract: Generated operational programs are often validated with either a few hand-written examples or exhaustive regression suites. The former can miss sparse

researcharxiv-cs-ai

Tutorials

Feature Transformation Enhanced Jacobi Polynomial Graph Filtering for Graph Anomaly Detection

arXiv:2608.27144v1 Announce Type: new Abstract: In recent years, graph anomaly detection (GAD) based on frequency-domain filtering have achieved promising results. However, existing approaches still f

tutorialsarxiv-cs-ai

FedCMAPSS: A Benchmark for Federated Learning in Remaining Useful Life Estimation

model-releasesarxiv-cs-lg

arXiv:2608.26433v1 Announce Type: new Abstract: Data-driven prognostics and health management has emerged as a key enabler for Industry 4.0, yet the development of robust remaining useful life (RUL) e

Federated Adversarial Training with Transformers

arXiv:2206.02131v2 Announce Type: replace-cross Abstract: Federated learning (FL) has emerged to enable global model training over distributed clients' data while preserving its privacy. However, the

FIDA: Feature Instability-Driven Attack on Self-Supervised Facial Representation

arXiv:2608.26861v1 Announce Type: new Abstract: Self-supervised learning (SSL) models are vulnerable to backdoor attacks. However, the systemic risks they pose in face representation have received lit

applicationsarxiv-cs-cv

Agents

Finding the Right Evidence: Factor-Guided Coarse-to-Fine Reasoning for Long Videos

arXiv:2608.26355v1 Announce Type: new Abstract: While LVLMs rapidly improve, long-video question answering still remains challenging: relevant evidence is sparse, and question-relevant context often f

agentsarxiv-cs-cv

Fine-Tuning of Transformer models with Frames

arXiv:2608.26430v1 Announce Type: new Abstract: Parameter-Efficient Fine-Tuning (PEFT) strategies such as Low-Rank Adaptation (LoRA) are effective solutions for fine-tuning large-scale pre-trained mod

FireRedAudio: A General-Purpose Audio Language Model with Decoupled Continuous Representations for Understanding and Generation

model-releasesarxiv-cs-cl

arXiv:2608.24168v2 Announce Type: replace Abstract: A unified audio model must recognize and understand linguistic, paralinguistic, and environmental information while supporting speech synthesis and

FIRSTPASS: A Multi-Domain, Multi-Round Peer Review Dataset Grounded in Real Editorial Outcomes

arXiv:2608.26129v1 Announce Type: cross Abstract: Scientific peer review datasets have trained AI systems exclusively on Computer Science and Machine Learning venues, producing models that critique ab

Five Primitives for Governing Autonomous AI Agents at Runtime

arXiv:2608.26696v1 Announce Type: new Abstract: Enterprise deployments of autonomous AI agents inherit a control model built for human users and long-lived services, and the fit fails in three specifi

safetyarxiv-cs-ai

Fixed-Haven Reservation for Online Multi-Agent Pickup and Delivery in Dense Warehouses

model-releasesarxiv-cs-ro

arXiv:2608.26759v1 Announce Type: cross Abstract: Dense warehouses often contain single-lane aisles, dead ends, and tree-like guidepaths that leave little room for idle agents to wait without blocking

FLARE: A Failure-Aware Framework for Autonomous Correction and Recovery in Visual-Language Robotic Manipulation

arXiv:2608.26645v1 Announce Type: new Abstract: Vision-Language-Action Models~(VLAs) have demonstrated significant promise in generalizing to complex, long-horizon robotic manipulation tasks. However,

safetyarxiv-cs-ro

Hardware

FlashVLA: Streaming Action Decoding for Fast and Asynchronous VLA Inference

arXiv:2608.27384v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models are increasingly promising for robotic manipulation, yet their real-world deployment remains bottlenecked by high in

hardwarearxiv-cs-ro

FLAT: FLow-Aligned Training of Unrolled Networks for MRI Reconstruction

arXiv:2512.03020v3 Announce Type: replace Abstract: Unrolled networks are widely used in Magnetic Resonance Imaging (MRI) reconstruction for their efficiency. Structured as a series of neural network

FOCUS & RePAIR: Mitigating Text Degeneration via Token-Level Guidance for Pruned Large Language Models

arXiv:2608.26676v1 Announce Type: cross Abstract: Pruning is a practical approach to compress large language models (LLMs), but it can amplify text degeneration, especially repetition loops, even when

researcharxiv-cs-ai

FoldPipe: Bounded Remote Streaming of Native Molecular Shards with Asynchronous Prefetch

model-releasesarxiv-cs-lg

arXiv:2608.27029v1 Announce Type: cross Abstract: Training molecular machine-learning models on ephemeral or memory-constrained accelerator instances can require repeatedly retrieving preprocessed mol

Forward-Free Diffusion Language Models with BPTT-Free Looped Refinement

arXiv:2606.08357v2 Announce Type: replace Abstract: Diffusion language models generate text through iterative denoising, offering a powerful alternative to autoregressive generation. However, discrete

researcharxiv-cs-cl

From Accuracy to Robustness: A Study of Rule- and Model-based Verifiers in Mathematical Reasoning

arXiv:2505.22203v3 Announce Type: replace-cross Abstract: Trustworthy verifiers are essential for the success of reinforcement learning with verifiable reward (RLVR), which is the core methodology beh

From Atomic to Agentic: Towards Interpretable Evaluation of LLMs' Agentic Mathematical Capabilities

arXiv:2608.26950v1 Announce Type: new Abstract: Large Language Models (LLMs) are evolving from performing end-to-end mathematical reasoning to integrating agentic intelligence. However, most existing

From Reasoning to Pixels: Grounded Medical Multimodal LLMs for VQA and Segmentation

arXiv:2608.26856v1 Announce Type: cross Abstract: Although Multimodal Large Language Models (MLLMs) have demonstrated impressive performance in Medical Visual Question Answering (Med-VQA), their relia

From Sound to Symptom: Real-Time Respiratory Signal Understanding for Conversational Healthcare Agents

arXiv:2608.26163v1 Announce Type: cross Abstract: Cough events during live spoken conversations carry clinically valuable respiratory signals, yet existing dialogue systems treat them as acoustic nois

applicationsarxiv-cs-ai

Agents

From SQL to Knowledge Graphs: An LLM-Driven Multi-Agent Approach with Data Schema Improvement

arXiv:2608.26117v1 Announce Type: cross Abstract: RDBMS (Relational Database Management System) databases face several limitations, including slow execution with multi-hop queries and a lack of explai

agentsarxiv-cs-ai

From Static to Dynamic: Benchmarking Real-World Code Review with MCR-Bench

arXiv:2608.27442v1 Announce Type: cross Abstract: In real-world software development, code review typically involves iterative interactions between developers and reviewers to improve software quality

FU-Mamba: A Frequency-Enhanced Dynamic Scanning Framework for Oralscan Image Segmentation

arXiv:2608.26607v1 Announce Type: new Abstract: Oralscan image segmentation is essential for computer-aided diagnosis and treatment planning in digital dentistry. However, existing visual state space

G2D: Generative-to-Discriminative Collaborative Inference for Zero-Shot Image Classification

arXiv:2608.26744v1 Announce Type: new Abstract: Zero-shot classification needs efficient label retrieval and fine-grained visual reasoning, yet discriminative and generative vision-language models fai

GameWAM: A World Action Model for Video Games

arXiv:2608.26200v1 Announce Type: new Abstract: Modern video games combine first-person perception, rapid visual changes, persistent world state, and heterogeneous native controls. Existing game agent

researcharxiv-cs-ai

Gaussian Processes and Reproducing Kernel Hilbert Spaces: Connections and Equivalences

arXiv:2506.17366v2 Announce Type: replace-cross Abstract: This monograph studies the relations between two approaches using positive definite kernels: probabilistic methods using Gaussian processes, a

researcharxiv-cs-lg

Gaze Authentication: Factors Influencing Authentication Performance

arXiv:2509.10969v3 Announce Type: replace Abstract: This paper examines the key factors that influence the performance of state-of-the-art gaze-based authentication. Experiments were conducted on a la

Generative Monte Carlo Sampling for Constant-Cost Particle Transport

arXiv:2512.13965v1 Announce Type: cross Abstract: We present Generative Monte Carlo (GMC), a novel paradigm for particle transport simulation that integrates generative artificial intelligence directl

researcharxiv-cs-lg

Generative Semantic Scene Completion

arXiv:2608.26737v1 Announce Type: new Abstract: Outdoor LiDAR semantic scene completion (SSC) recovers a dense semantic voxel grid from a scan observing 1% of the target volume, under class imbalance

Geo-LoRA: Geometry-Aware Subspace Evolution for Low-Rank Adaptation in Continual Learning

model-releasesarxiv-cs-cv

arXiv:2608.26960v1 Announce Type: new Abstract: Rehearsal-free class-incremental learning (CIL) with LoRA adapters remains challenging because the low-rank subspaces updated across tasks evolve withou

GeoMAD: Geometry-Aware Multi-View Anomaly Detection via Deformable Fusion and Distributional Alignment

arXiv:2608.26724v1 Announce Type: new Abstract: Multi-view anomaly detection (MvAD) detects defects by exploiting complementary observations from multiple camera viewpoints. The central challenge is t

safetyarxiv-cs-cv

Glass Surface Detection Grounded in 3D Visual Geometry

arXiv:2608.26752v1 Announce Type: new Abstract: Glass surface detection (GSD) is critical for scene understanding and reconstruction, and yet remains challenging due to the transparency and reflectivi

Global universality via discrete-time signatures

model-releasesarxiv-cs-lg

arXiv:2603.09773v2 Announce Type: replace-cross Abstract: We establish global universal approximation theorems for non-anticipative and general path-dependent functionals on spaces of piecewise linear

GRAFT: Grounded and Efficient Online Reinforcement Adaptation for Fine-Grained Robot Manipulation

arXiv:2608.27079v1 Announce Type: new Abstract: Pretrained vision-language-action (VLA) policies provide strong priors for robot manipulation, yet adapting them online to fine-grained biomedical tasks

safetyarxiv-cs-ro

GRAIN: Bridging Name and Narrative Shifts in Real-World Graph Reasoning through Invariance-Rewarded Agentic RL

arXiv:2608.27142v1 Announce Type: new Abstract: Despite their potential in standardized graph tasks, Large Language Models (LLMs) remain brittle to real-world shifts in node identifiers and task formu

Graph-Based Modeling of Financial Volatility Dynamics

arXiv:2608.26127v1 Announce Type: cross Abstract: Accurate forecasting of realized volatility (RV) is crucial for risk management and derivatives pricing. Although the implied volatility (IV) surface

applicationsarxiv-cs-cl

Graph-Based Pseudo-multimodal Contrastive Learning for 12-Lead ECG Representations

arXiv:2608.26964v1 Announce Type: new Abstract: 12-lead electrocardiogram (ECG) is a standard, non-invasive examination widely used for diagnosing coronary artery disease, where clinical interpretatio

researcharxiv-cs-lg

Graph-Guided Selective Unlearning for Language Models: Controlling Support Routes Beyond Forget Seeds

arXiv:2608.26743v1 Announce Type: new Abstract: Enterprises fine-tune language models on proprietary data that may later require removal due to privacy, contractual, or compliance obligations. Selecti

Agents

GraphMemix: Query-Aware Evidence Forests for Long-Term Multimodal Agent Memory

arXiv:2608.26983v1 Announce Type: new Abstract: Organizing long-term memory for multimodal agents remains challenging because existing methods either suffer from expensive question-agnostic offline su

agentsarxiv-cs-ai