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arXiv:2608.18185v1 Announce Type: cross Abstract: Fine-grained recognition often involves hierarchical label spaces, where a model may be confident about a coarse semantic concept while remaining unce

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Model Releases

Institutional Books - Enriched Text: A customizable multilingual open-source pipeline for denoising, deduplicating, and annotating OCR text at scale

DGX agent

arXiv:2608.19026v1 Announce Type: new Abstract: Released in 2025, Institutional Books: Harvard Library (IB-HL) is a collection of 983,004 volumes (242B o200k_base tokens), originally digitized through

model-releasesarxiv-cs-cl

20 Aug 2026

Institutional Newspapers Pipeline: Deriving billions of high quality tokens from historical newspapers

model-releasesarxiv-cs-cl

arXiv:2608.18972v1 Announce Type: new Abstract: Historical newspapers are an abundant record of public life, but their dense, irregular and sometimes noisy layouts make computational access to these m

LongNovel: A Multi-Scale Benchmark for Hallucination Detection in Long-Context Novel Summarization

model-releasesarxiv-cs-cl

arXiv:2608.18082v1 Announce Type: new Abstract: Although context windows have expanded significantly in recent years, hallucinations in long-context summarization remain a challenge. Long novels are b

Metrics That Write Themselves: Evolving an Evaluator from Its Own Blind Spots

arXiv:2608.18744v1 Announce Type: new Abstract: Agents improve quickly against a reliable automatic metric and stall without one, and the applications that need them most, report generation among them

Multi-Class Electrical and Mechanical Fault Classification Using Random Convolutional Kernels

arXiv:2608.18716v1 Announce Type: new Abstract: Diagnosing faults in rotating machinery is essential for ensuring the reliability of industrial processes. Random convolutional kernel-based Time Series

Local Ai

OptiModNet: A UNet-Transformer Hybrid with Grouped-Query and Channel Attention for Optic Disc and Cup Segmentation

arXiv:2608.18516v1 Announce Type: cross Abstract: Precise segmentation of the optic disc and cup is critical for the early detection and diagnosis of glaucoma. However, achieving consistently high per

local-aiarxiv-cs-ai

Local Ai

ORBITER: Conflict-Aware Decision-Making for Agentic Last-Mile Delivery

arXiv:2608.18846v1 Announce Type: new Abstract: Last-mile delivery aims to handle dynamically arriving orders with couriers while modeling complex spatial and temporal correlations. Recent learning-ba

local-aiarxiv-cs-ai

Safety

RDFdL: Integrating RDF with Differential Dynamic Logic

arXiv:2608.18165v1 Announce Type: new Abstract: Knowledge graphs modeled in RDF are powerful for describing static knowledge, but they cannot capture or reason about the dynamic behavior of physical s

safetyarxiv-cs-ai

Tutorials

Role-Conditioned Sub-Token Routing for Efficient Vision-Language-Action Policies

arXiv:2608.18410v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models process long multimodal token sequences, making inference expensive in both memory and computation. Existing efficie

tutorialsarxiv-cs-lg

RVLoss: Runoff Vote Loss for Self-Supervised LiDAR Scene Flow Estimation

arXiv:2608.18864v1 Announce Type: new Abstract: LiDAR scene flow estimates point-wise motion between two consecutive scans, referred to as the source and target. Leading self-supervised methods typica

SIDScope: A Diagnostic Resource for Semantic-ID Interfaces in Generative Recommendation

arXiv:2608.18779v1 Announce Type: cross Abstract: Semantic-ID mappings are reusable interfaces between item tokenizers and generative recommenders, yet released mappings rarely state whether they are

SPADE: Self-Play in Adaptive Synthetic Executable Environments

arXiv:2608.19197v1 Announce Type: cross Abstract: Continuous self-improvement requires an ever-expanding pool of self-generated, diverse, adaptive goals. For language agents, existing training environ

Applications

Test-Time Scaling in the Wild: Why Exploitation, Not Exploration, Is the Bottleneck

arXiv:2608.18931v1 Announce Type: cross Abstract: Test-time scaling (TTS) improves language model outputs by spending additional inference compute - generating multiple candidates, searching over part

applicationsarxiv-cs-ai

Tianmu-TC: Physics-constraints Generative Artificial Intelligence for Global Tropical Cyclone Forecasting

arXiv:2608.18500v1 Announce Type: new Abstract: Tropical cyclones (TCs) pose severe risks from strong winds and heavy rainfall. However, forecasting their track and intensity remains challenging due t

researcharxiv-cs-lg

When Do LLMs Actually Help? Evaluating LLMs as Data Quality Annotators

arXiv:2608.18158v1 Announce Type: cross Abstract: LLMs have been increasingly used to catch data quality issues automatically, but we know very little about how consistent these judgments actually are

AppendiGrade: An XAI-Enhanced Deep Learning Framework for Grading Appendicitis in Ultrasound with Gaussian Blur and Grad-CAM

arXiv:2608.17923v1 Announce Type: new Abstract: Appendicitis is one of the most common abdominal emergencies worldwide and requires prompt diagnosis and treatment to prevent life-threatening condition

researcharxiv-cs-cv

ARASH: Adaptive Retrieval And Shot Selection for Tabular Prediction

arXiv:2608.17856v1 Announce Type: new Abstract: Tabular prediction is a critical task across numerous applications. The recent success of large language models has sparked various approaches for adapt

AViTS: Adaptive Spatiotemporal Token Selection for Efficient Dynamic-Resolution Generation

arXiv:2608.17995v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) achieve high-quality generation but are costly due to iterative sampling. Dynamic-resolution sampling reduces early-stage

B-Spline Embedded Structure Learning for 3D Tooth Segmentation

arXiv:2608.17291v1 Announce Type: new Abstract: Accurate 3D tooth segmentation forms the cornerstone of digital dentistry, yet it remains a formidable challenge due to the inherent intricacy of real-w

Agents

CARA: Cognitive Adaptive Recommendation Agent

arXiv:2608.16919v1 Announce Type: cross Abstract: Recent advances in large language models and agent-based recommendation frameworks have introduced new opportunities for more flexible and context-awa

agentsarxiv-cs-ai

CFB-GBM v2.0: An Augmented Longitudinal Dataset for Multi-Modal Glioblastoma Segmentation, Radiomics, and RANO Progression Tracking

arXiv:2608.17884v1 Announce Type: new Abstract: Glioblastoma (GBM) is the most aggressive primary brain tumor in adults, with a median overall survival of 15 months. Longitudinal, multi-modal imaging

Code as Representation: A Compilable Parsing Paradigm for Academic Documents

model-releasesarxiv-cs-cl

arXiv:2608.17550v1 Announce Type: cross Abstract: Academic papers are a primary carrier of scientific knowledge, yet most of this knowledge remains locked in PDFs that are optimized for human reading

Cognitive Graph Intelligence for Adaptive and Robust DDoS Attack Detection in Next Generation Networks

arXiv:2608.17352v1 Announce Type: new Abstract: Distributed Denial-of-Service (DDoS) attacks threaten network availability, requiring a cognitive detection process that senses traffic, infers intent,

Debate Training Reduces Reward Hacking in RLAIF

arXiv:2608.17776v1 Announce Type: new Abstract: We demonstrate that RL finetuning an LLM using debate, a two-player adversarial game between a generator and a critic adjudicated by a weaker LLM judge,

Dynamic Entanglement-Weighted Pruning for Quantum Federated Unlearning in Supply-Chain Risk Prediction

arXiv:2608.17069v1 Announce Type: cross Abstract: Federated deployments of variational quantum classifiers are attractive for cross-organisation risk prediction in supply chains, because raw data neve

Efficient RLVR Scheduling via Graph-Structured Online Difficulty Estimation

arXiv:2608.17941v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) improves the reasoning capabilities of large language models but relies on costly rollout explor

Evaluating RL Explainability Methods by How Much They Help Fix Bugs in Agents

arXiv:2608.17524v1 Announce Type: new Abstract: This preliminary paper outlines a planned evaluation benchmark for Explainable Reinforcement Learning (XRL) methods. Current evaluations rely on functio

Expanding the Lexicon of Ge'ez Based African Languages: A Comparative Study of Amharic and Tigrinya

arXiv:2607.15209v2 Announce Type: replace Abstract: Multilingual pre-trained language models such as XLM-R perform well for major languages but struggle with low-resource Ge'ez-script languages, large

researcharxiv-cs-cl

Exploring Efficient Open-Vocabulary Segmentation in the Remote Sensing

arXiv:2509.12040v3 Announce Type: replace-cross Abstract: Open-Vocabulary Remote Sensing Image Segmentation (OVRSIS), an emerging task that adapts Open-Vocabulary Segmentation (OVS) to the remote sens

Expressivity In Multimodal Contrastive Learning

arXiv:2608.17203v1 Announce Type: cross Abstract: Contrastive learning has become a cornerstone of modern representation learning, powering CLIP-style models that underpin text-to-image generation, vi

researcharxiv-cs-lg

Safety

From Adoption to Deployment: A Qualitative Study on AI Integration in Software Development Practice

arXiv:2607.16660v2 Announce Type: replace-cross Abstract: The increasing adoption of Large Language Models (LLMs) as AI components in modern software systems introduces distinct security risks to the

safetyarxiv-cs-ai

G-ReAct: Graph-Guided Deep Search via Structure-State Co-Evolution

arXiv:2608.01324v2 Announce Type: replace Abstract: Deep search has become a fundamental capability of large language models (LLMs) for solving open-domain complex tasks. However, existing approaches

Gradient Heterogeneity Complements Hessian Heterogeneity in Transformer Optimization

arXiv:2502.00213v5 Announce Type: replace-cross Abstract: Transformers are difficult to optimize with stochastic gradient descent (SGD) and largely rely on adaptive optimizers such as Adam. Despite ex

GxP-Agent: Process-DAG Topology for Reliable Clinical Trial Programming with LLM Agents

arXiv:2608.16890v1 Announce Type: new Abstract: Clinical trial programming -- transforming study protocols into analysis-ready datasets under CDISC standards -- is a bottleneck in regulatory submissio

HeteRo-Select: Informativeness as the Participation Driver in Heterogeneous Federated Learning

arXiv:2508.06692v3 Announce Type: replace Abstract: Federated learning systems typically allocate gradient compression by link speed. This is sensible when bandwidth and data informativeness align. Ho

HyPE-GT: where Graph Transformers meet Hyperbolic Positional Encodings

arXiv:2312.06576v2 Announce Type: replace Abstract: Graph Transformers (GTs) facilitate the comprehension of complex relationships on graph-structured data by leveraging self-attention of the possible

Leveraging Association Context Retrieval in Knowledge Edit- ing to Build White-Box Attacks on LLMs

arXiv:2608.17836v1 Announce Type: new Abstract: As large language models (LLMs) are granted increasing autonomy, it is essential to investigate methods that can induce unsafe behavior. We propose a no

researcharxiv-cs-lg

LLMs for Medical Consultation Are Evaluated Too Late: The Preformulation Gap

arXiv:2608.17330v1 Announce Type: new Abstract: Large language models for medical consultation are often evaluated after a clinical problem has already been made clear, although real consultations may

LSem2Vec: A Simple yet Effective Two-Stage Approach for Source Code Embedding

arXiv:2409.14644v4 Announce Type: replace-cross Abstract: The advent of large language models (LLMs) has significantly advanced artificial intelligence in software engineering, with source code embedd

Safety

Margin-Regularized Structured Semantic Alignment for Brain-Language Correspondence

arXiv:2608.16975v1 Announce Type: new Abstract: With the rapid advancement of large language models, brain-language decoding has achieved remarkable progress. However, it remains unclear whether decod

safetyarxiv-cs-cl

Maximum Tsallis Entropy Distributions for Robust and Efficient Sparse Learning from Correlated Data

arXiv:2608.17244v1 Announce Type: cross Abstract: This paper addresses the limitations of Gaussian distribution assumptions in statistical sparse learning, particularly in modeling correlated and hete

MoRA: Mobility as the Backbone for Geospatial Representation Learning at Scale

arXiv:2506.01297v5 Announce Type: replace Abstract: Representation learning of geospatial locations remains a core challenge in achieving general geospatial intelligence, with increasingly diverging p

Plug-and-Play Traffic Element Awareness for End-to-End Autonomous Driving

arXiv:2608.18035v1 Announce Type: new Abstract: Traffic elements such as traffic lights and road signs play a fundamental role in human driving decisions and should naturally influence end-to-end driv

Policy Optimization and Statistical Inference for Online Contextual Matrix Games

arXiv:2608.17173v1 Announce Type: cross Abstract: Online decision making often requires navigating a landscape shaped by both dynamic contexts and strategic interactions. In competitive pricing, for e

Preference Is Not Intervention: The Structure and Stability Boundaries of Reader-Specific Evidence Utility

arXiv:2608.17781v1 Announce Type: new Abstract: ML systems increasingly condition decisions on downstream model identity, but this is useful only if model-specific differences form reusable structure

researcharxiv-cs-cl

SFMformer: A Spatial-Frequency Modulation Transformer for Lightweight Image Super-Resolution

arXiv:2608.17966v1 Announce Type: new Abstract: Sparse attention mechanisms, which score all token pairs but propagate only the strongest, now underpin the most efficient Transformers for lightweight

Agents

SkillEffect: Checked Lowering for Memory-Bounded Agent Tools

arXiv:2608.17007v1 Announce Type: new Abstract: Agent Skills can specify procedural and resource obligations for tool use, and language models instantiate them as concrete programs. However, when mode

agentsarxiv-cs-ai