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On the missing benchmarks layer and a potential solution

arXiv:2608.02996v1 Announce Type: new Abstract: Latin America is missing a foundational layer for native AI development: the benchmark layer. The benchmark layer does two things no other layer can - i

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On the missing data layer and a potential solution

DGX agent

arXiv:2608.02949v1 Announce Type: new Abstract: Latin America is missing two foundational layers of AI infrastructure: the dataset layer and the benchmark layer. This paper targets the dataset layer.

model-releasesarxiv-cs-ai

5 Aug 2026

On the Non-Specificity of Statistical Measures Used in Script Decipherment

arXiv:2608.02999v1 Announce Type: new Abstract: Statistical regularities are routinely offered as evidence that undeciphered sign systems encode language; the Indus script debate is the canonical exam

researcharxiv-cs-cl

Pattern over Pixels: Measuring Pattern Completion Bias in Multimodal Code Generation

arXiv:2608.03691v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) are increasingly used to translate webpage screenshots into front-end code, but repeated UI patterns may sway

Local Ai

Prediction-Enhanced Monte Carlo: A Machine Learning View on Control Variate

arXiv:2412.11257v4 Announce Type: replace-cross Abstract: For many complex simulation tasks spanning areas such as healthcare, engineering, and finance, Monte Carlo (MC) methods are invaluable due to

local-aiarxiv-cs-lg

Applications

PRISM: Powerful Time Series to Image (TS2I) Representations for Multivariate Anomaly Detection

arXiv:2608.03926v1 Announce Type: cross Abstract: Time series anomaly detection (TSAD) underpins applications in predictive maintenance, finance, and cloud computing, however performance remains sensi

applicationsarxiv-cs-ai

Quantization Effects on Biomedical LLM Reliability

model-releasesarxiv-cs-lg

arXiv:2608.03854v1 Announce Type: new Abstract: When decoder language models are used as classifiers, predicted class probabilities depend on implementation choices, including the prompt template, ver

Reachability Is Not Realization: Tracing the Sources of LLM Benchmark Gains

arXiv:2608.03219v1 Announce Type: new Abstract: Benchmark gains are often treated as evidence of greater LLM capability. Yet the same gain can reflect different changes in model behavior. A model may

Rethinking Self-Evolving Agent Skills: Feedback Dynamics over Multiple Rounds

arXiv:2608.02636v1 Announce Type: cross Abstract: Self-evolving skill systems promise to improve agents by turning execution feedback into persistent skill updates without changing the underlying mode

Route-Align-Verify for Functional Correctness in Code Generation

arXiv:2608.03341v1 Announce Type: cross Abstract: Large language models (LLMs) have substantially improved code generation, yet achieving strong functional correctness remains difficult, especially fo

Self-Guided Adaptive Safety Alignment: Synthesizing and Internalizing Guidelines in Reasoning Models

arXiv:2511.21214v4 Announce Type: replace-cross Abstract: Explicit safety policies can improve reasoning-model safety, but their effective coverage may lag behind evolving jailbreak strategies. We stu

Self-Supervised Representation-Guided Generative Dataset Distillation

arXiv:2608.03218v1 Announce Type: cross Abstract: Dataset distillation compresses a large training set into a compact synthetic set while retaining its downstream utility. Most existing methods target

Socially Grounded Agentic AI: Coordinating Plural Perspectives through Social Theory

arXiv:2608.03910v1 Announce Type: new Abstract: As AI systems are deployed across increasingly diverse social contexts, alignment can no longer be framed as the optimization of a single, unified set o

SpreadMark: Robust Image Watermarking via Spread-Spectrum Embedding

arXiv:2608.03165v1 Announce Type: cross Abstract: Invisible image watermarks are increasingly used for deepfake detection and provenance tracking, where they must survive not only incidental distortio

researcharxiv-cs-cv

Surrogate Substitution Preserves PHI Detectability: A Multi-Detector Equivalence Study

arXiv:2608.03172v1 Announce Type: new Abstract: Structure-preserving de-identification replaces protected health information (PHI) with realistic same-type surrogates -- 'Anna S.' becomes 'Maria S.',

researcharxiv-cs-ai

T2VAttack: Adversarial Attack on Text-to-Video Diffusion Models

arXiv:2512.23953v2 Announce Type: replace Abstract: The rapid evolution of Text-to-Video (T2V) diffusion models has driven remarkable advancements in generating high-quality, temporally coherent video

safetyarxiv-cs-cv

Test-Time Augmentation for Tabular-to-Image Classifiers under Distribution Shifts

model-releasesarxiv-cs-cv

arXiv:2608.03557v1 Announce Type: new Abstract: Tabular-to-image methods that convert tabular data into visual representations have emerged as a novel paradigm for leveraging the high performance of d

Towards Reliable and Reproducible Fetal Brain Biometry: A Deep Learning Approach Using MRI

arXiv:2608.03724v1 Announce Type: new Abstract: Fetal brain biometry is essential for quantitative assessment of brain development, supporting gestational age estimation, developmental monitoring, and

researcharxiv-cs-cv

Unequal Verdicts: Investigating Gender Bias in LLM-Based Fake News Detection

arXiv:2608.03627v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used for automated fact-checking, yet their susceptibility to gender bias in this context remains underexp

UniPASE: A Generative Model for Universal Speech Enhancement with High Fidelity and Low Hallucinations

arXiv:2604.14606v2 Announce Type: cross Abstract: Universal speech enhancement (USE) aims to restore speech signals from diverse distortions across multiple sampling rates. We propose UniPASE, an exte

researcharxiv-cs-ai

UrbanAgent: A Tool-Augmented Agent for Cross-System Urban Tasks

arXiv:2608.03018v1 Announce Type: new Abstract: Modern cities rely on an increasing number of digital services to operate, but residents' daily needs are still difficult to meet. Services are fragment

When Policies Change Probabilities: Modular Decision-Making for LLM Code Review

arXiv:2608.02677v1 Announce Type: cross Abstract: LLM code reviewers often estimate patch risk and make approval decisions in one prompt. A probability should depend on evidence; costs should determin

A Benchmark Dataset for MLLM-Generated Image Detection: GPT Image2 & Nano Banana2

model-releasesarxiv-cs-cv

arXiv:2608.01258v1 Announce Type: new Abstract: The realism of images generated by multimodal large language models (MLLMs), such as GPT Image2 and Nano Banana2, has improved rapidly in recent years.

A Heuristic Perspective on Debiasing Language Models

arXiv:2608.00622v1 Announce Type: new Abstract: Language models (LMs) often acquire various biases during pre-training and may express them in interactions, potentially causing social harm. Existing m

safetyarxiv-cs-cl

ACE-GraphRAG: Agentic Context Engineering for Hierarchical GraphRAG

arXiv:2608.01269v1 Announce Type: new Abstract: Hierarchical Graph Retrieval-Augmented Generation (GraphRAG) organizes corpus knowledge at multiple levels of granularity, yet fixed context constructio

safetyarxiv-cs-cl

AdaThinkV: Adaptive Thinking for Token-Efficient Video Reasoning

arXiv:2608.01980v1 Announce Type: new Abstract: Chain-of-thought (CoT) reasoning can improve performance on difficult video questions but often wastes decoding tokens on simple ones. We study whether

safetyarxiv-cs-cv

Agents

Agentic Bayesian Optimization through Surrogate-Augmented Autoresearch

arXiv:2608.00316v1 Announce Type: new Abstract: Bayesian optimization (BO) has become the standard tool for sample-efficient optimization and owes its efficiency to uncertainty-aware search driven by

agentsarxiv-cs-lg

An AI-Based Decision-Support Pipeline for Day-Ahead Photovoltaic Forecasting

arXiv:2608.02088v1 Announce Type: new Abstract: Reliable photovoltaic (PV) forecasts are needed for low-carbon energy systems, but newly deployed sites often have short, imperfect records. This makes

safetyarxiv-cs-lg

An Evidence-Grounded Retrieval-Augmented Transformer Framework for Health Misinformation Verification

arXiv:2608.02310v1 Announce Type: new Abstract: The rapid spread of false and misleading health information through digital platforms has become a major public health challenge, particularly during in

researcharxiv-cs-cl

Auditable Release Control for Pedagogical Leakage in LLM Tutors

arXiv:2608.00515v1 Announce Type: cross Abstract: Large language model tutors can be correct and helpful yet disclose an answer or decisive reasoning before that disclosure is authorized. We formalize

AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling

arXiv:2608.02602v1 Announce Type: new Abstract: Language remains an outlier in generative modeling: while images, video, and audio are increasingly modeled in continuous latent spaces, text generation

Automated ECG Interval Measurement and Wave Delineation Using Fast Fourier Convolution ResNet

arXiv:2608.00058v1 Announce Type: cross Abstract: Accurate measurement of ECG intervals, including PR, QRS duration, and QT/QTc, is central to cardiac diagnosis, yet the published ECG delineation lite

safetyarxiv-cs-lg

Automatic Annotation of Ancient Greek Vowel Length

arXiv:2608.01935v1 Announce Type: new Abstract: Prior work in Ancient Greek NLP relies on corpora that do not disambiguate the phonemic vowel length of alpha, iota, and ypsilon, together known as the

Bagpiper: Solving Open-Ended Audio Tasks via Rich Captions

arXiv:2602.05220v4 Announce Type: replace Abstract: Current audio foundation models typically rely on rigid, task-specific supervision (e.g., speech recognition), addressing isolated factors of audio

Benchmarking Sheaf Neural Networks for Inductive Tasks

model-releasesarxiv-cs-lg

arXiv:2608.02558v1 Announce Type: new Abstract: Sheaf Neural Networks (SNNs) generalize message passing by replacing scalar edge weights of standard Graph Neural Networks (GNNs) with learnable, edge-d

Tutorials

Beyond Gene Reconstruction: Learning Cell Representations through Complementary Transcriptomic Views

arXiv:2608.00985v1 Announce Type: new Abstract: The rapid growth of single-cell transcriptomic data has enabled the development of foundation models pretrained primarily by reconstructing masked expre

tutorialsarxiv-cs-lg

Breaking Diversity Collapse in Spiking Pseudo-Ensembles for Efficient OOD Detection in Remote Sensing

arXiv:2608.01090v1 Announce Type: new Abstract: Spiking Neural Networks (SNNs) are attractive for resource-constrained remote-sensing systems, but reliable out-of-distribution (OOD) detection remains

researcharxiv-cs-lg

BRIC-Net: Boundary-Reliable Illumination-Color Interaction for Remote Sensing Image Deshadowing

arXiv:2608.00682v1 Announce Type: new Abstract: Shadows in remote sensing images obscure surface appearance and disrupt radiometric continuity, reducing the reliability of visual interpretation and do

researcharxiv-cs-cv

Bridging the English-Arabic Medical Knowledge Gap: Targeted Low-Rank Adaptation via Causal Layer Selection

arXiv:2608.00207v1 Announce Type: new Abstract: Large Language Models (LLMs) perform strongly in English medical tasks but degrade substantially in Arabic, a gap widely attributed to limited training

Applications

Can Urban Blight Be Accessed with Vision-language Models: A Case Study in Detroit

arXiv:2608.01753v1 Announce Type: new Abstract: Addressing urban blight has seen increased focus in the past 15 years. Assessing urban blight is essential for guiding urban planning, targeting rehabil

applicationsarxiv-cs-cv

Capability Provenance in Language Models: A Case Study in Social Reasoning

arXiv:2606.19625v2 Announce Type: replace Abstract: We use training-data attribution as an interpretable tool for capability discovery, mapping which regions of the pretraining corpus support social-r

Characterizing Treatment-Context Medication Evidence Across Clinic Notes and Structured EHR Medication History

arXiv:2608.01570v1 Announce Type: new Abstract: Clinic notes and structured electronic health record (EHR) medication history often contain different medication information. Same-visit disagreement be

researcharxiv-cs-cl

Cooperative Coevolution for Resource-Constrained Agentic LLM Post-Training

model-releasesarxiv-cs-lg

arXiv:2608.02391v1 Announce Type: cross Abstract: Tool-using large language model (LLM) agents produce long, multi-turn trajectories, making gradient-based post-training memory-intensive. Evolution st

CRISP: Critical Step Perception for Training Efficient Deep Search Agents

arXiv:2608.01867v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly extended into deep search agents that solve complex questions through multi-step interaction with external

safetyarxiv-cs-cl

Agents

DecoupleGS: Interactive 3D Gaussian Splatting for End-to-End Autonomous Driving Testing

arXiv:2608.01761v1 Announce Type: new Abstract: End-to-end (E2E) autonomous driving algorithms require rigorous closed-loop validation in simulation environments offering high visual fidelity, strong

agentsarxiv-cs-cv

Deep Learning for Retinal Degeneration Assessment: A Comprehensive Analysis of the MARIO Challenge

model-releasesarxiv-cs-cv

arXiv:2506.02976v4 Announce Type: replace Abstract: The MARIO challenge, held at MICCAI 2024, focused on advancing the automated detection and monitoring of age-related macular degeneration (AMD) thro

Local Ai

Device-First Feedback: Toward Mobile-Native LLM-Driven Neural Architecture Search

arXiv:2608.00078v1 Announce Type: new Abstract: Deploying convolutional neural networks generated by large language models (LLMs) on real mobile hardware requires more than GPU validation accuracy: IN

local-aiarxiv-cs-cv

Agents

Diagnosing Search Behavior and Failure Modes in Long-Horizon Search Agents

arXiv:2608.01913v1 Announce Type: cross Abstract: Deep search agents answer difficult information-seeking questions by iteratively issuing search queries to gather supporting evidence, but it remains

agentsarxiv-cs-cl