All entries

Falling Behind Drives Unsafe Development in an Idealised AI Race Experiment

arXiv:2607.26034v1 Announce Type: new Abstract: Technological races create tension between speed and safety: actors may gain by moving faster than competitors, even when risky development is harmful.

safetyarxiv-cs-ai

Fast, accurate, and differentiable: a neural-network surrogate for NRSur7dq4 precessing binary black hole waveforms

DGX agent

arXiv:2607.24960v1 Announce Type: cross Abstract: We present a neural network surrogate model that emulates the NRSur7dq4 gravitational waveform model for precessing binary black hole mergers. The sur

model-releasesarxiv-cs-lg

29 Jul 2026

Few-Shot Open-Vocabulary Remote Sensing Segmentation via Textual Inversion

model-releasesarxiv-cs-cv

arXiv:2607.25563v1 Announce Type: new Abstract: Open-vocabulary segmentation labels arbitrary categories from a text query without per-class training, yet on remote sensing imagery it underperforms on

FFNet: MetaMixer-based Efficient Convolutional Mixer Design

arXiv:2406.02021v3 Announce Type: replace-cross Abstract: Transformer, composed of self-attention and Feed-Forward Network, has revolutionized the landscape of network design across various vision tas

FIDAC: An Easy-to-use Pipeline to Extract and Interpret Interpersonal Distance From Video

arXiv:2607.25146v1 Announce Type: new Abstract: The distance between persons reveals significant information about their perception of each other. However, such information is not easily extractable a

FinAbstain: Uncertainty-Calibrated Multimodal RAG for Selective Financial Forecasting

arXiv:2607.24875v1 Announce Type: new Abstract: Large language models (LLMs) can synthesize financial narratives but may express high confidence when evidence is sparse, stale, or contradictory. This

Finding Optimal Cost-Bounded Plan Reductions: Refined Model

arXiv:2607.25484v1 Announce Type: new Abstract: In some real applications a plan may later become unfeasible due to newly imposed budget constraints, yet, at the same time, using only the original act

Fine-Grained Food Image Understanding via Target-Aware Data Alignment

arXiv:2607.25794v1 Announce Type: new Abstract: Fine-grained food visual--semantic understanding requires models to capture subtle distinctions across ingredients, cooking methods, doneness, color, te

safetyarxiv-cs-cv

FIRMGrasp: A Friction-Informed Risk Margin for Robust Grasp Synthesis

arXiv:2607.25049v1 Announce Type: new Abstract: Classical grasp quality metrics assume a single deterministic friction coefficient, so they cannot predict whether a grasp retains force closure across

researcharxiv-cs-ro

First Kimi K3 results on home lab ~ 4t/s

model-releasesr-localllama

I've got better results than expected for 768gb DDR5 and 2x5090. Using fork https://github.com/pwilkin/llama.cpp/tree/kimi-k3-text and https://huggingface.co/GrEarl/Kimi-K3-GGUF Q2_K quant. Prefill sp

FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model

arXiv:2607.25791v1 Announce Type: new Abstract: Falls represent a critical public health challenge, and accurate detection of the impact moment when an individual hits the ground is crucial for timely

Local Ai

FlashEvaluator: Expanding Search Space with Parallel Sequence-Level Evaluation

arXiv:2603.02565v2 Announce Type: replace-cross Abstract: The Generator-Evaluator (G-E) framework generates K candidate sequences and uses an evaluator to select the highest-scoring one, which is wide

local-aiarxiv-cs-cl

Food Image Segmentation with LLM-Derived Ingredient Labels and Multimodal Fusion

model-releasesarxiv-cs-cv

arXiv:2607.25820v1 Announce Type: new Abstract: Food image segmentation plays a vital role in health-related applications such as nutrition tracking and personalized health monitoring. However, existi

Forensic Reproducibility Audit of a Radiology Vision-Language Model Benchmark: From Intended Protocol to Released Artifact

model-releasesarxiv-cs-cl

arXiv:2607.25589v1 Announce Type: cross Abstract: Medical-imaging AI benchmarks combine datasets, DICOM rendering, prompts, provider APIs, automated labels, statistical code, manuscripts, and reposito

FORGE: Frame Orthogonality in Relevance Geometry for Long-Form Video Understanding

arXiv:2607.25266v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have enabled long-form video understanding at a scale that was not previously possible. However, the density of

Forgetting Is Not a Fix: Path Dependence in Sequential Engram Editing

arXiv:2607.24805v1 Announce Type: cross Abstract: AI Engram (Kwon et al., 2026) formalizes the four engram criteria of neuroscience as a constrained inverse problem in weight space and solves it close

Foundation Models for EEG Are Blind to Long-Range Temporal Correlations: A Spectral-Temporal Dissociation Behind Their Cross-Population Fragility

arXiv:2607.24834v1 Announce Type: cross Abstract: Objective. Electroencephalography (EEG) foundation models (FMs) are trained to reconstruct or contrastively align short patches, then pooled into a fi

FREPix: Frequency-Heterogeneous Flow Matching for Pixel-Space Image Generation

arXiv:2605.06421v2 Announce Type: replace Abstract: Pixel-space diffusion has re-emerged as a promising alternative to latent-space generation because it avoids the representation bottleneck introduce

Freq-RemoteVAR: Next-Frequency Autoregressive Modeling for Remote Sensing Change Detection

arXiv:2607.25815v1 Announce Type: new Abstract: Remote sensing change detection aims to identify land-cover changes from bi-temporal images. Most existing methods follow a one-shot dense prediction pa

From Cellular Responses to Pharmacological Domains: Multimodal Zero-Shot Drug Representation Learning

arXiv:2607.25322v1 Announce Type: new Abstract: Multimodal drug discovery enables drug representation learning beyond chemical structure by incorporating cellular responses such as gene expression and

From CUDA to MLX: How K-Search Brings Decades of Kernel Expertise to Apple Silicon

model-releasesberkeley-ai-research

Figure 1: CUDA-to-MLX optimization translation map. CUDA optimization knowledge can be translated into architecture-native MLX strategies rather than copied instruction-for-instruction. We face a new

From Deterministic to Generative Deep Learning for Urban Air Quality Reconstruction from Sparse Observations

arXiv:2607.25687v1 Announce Type: cross Abstract: Full-field reconstruction of air pollution is essential for evaluating pollution exposure and supporting public health decision-making. However, the c

From Dyad to Triad: Eliciting XAI Requirements in Stroke Rehabilitation

arXiv:2607.25423v1 Announce Type: cross Abstract: Eliciting explainable AI (XAI) requirements from stroke survivors presents a methodological challenge with direct implications for the design of trust

safetyarxiv-cs-ai

Tutorials

From Idea to Classroom in Days: Using 'Vibe Coding' to Create a Programming Process Visualizer from IDE Activity Logs

arXiv:2607.24757v1 Announce Type: cross Abstract: This paper reports on the rapid development and classroom deployment of a Thonny log visualizer built using AI-assisted ``vibe coding'' to make studen

tutorialsarxiv-cs-ai

Agents

From Naive RAG to Deep Agentic Retrieval: An Evolving Context Engineering Pipeline for Regulatory Compliance

arXiv:2607.24791v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) is the dominant paradigm for applying large language models (LLMs) to enterprise document corpora, yet naive impl

agentsarxiv-cs-ai

Agents

From Signal to PR: What if your agents got better every time they failed?

Signal, a managed agent built into Arize AX, continuously reviews production traces, surfaces ranked issues with evidence and proposed fixes, and — with Managed Agents — can carry investigations into

agentsarize-ai

From Training to Deployment: Post-Hoc Causal Feature Identification via Sensitivity Ratios

arXiv:2607.25546v1 Announce Type: new Abstract: Given a model that is already trained, which features does it rely on causally versus spuriously? Existing methods require access to the training proced

Fundamental Recovery Bounds for SPAD Signals under Stationary Flux

arXiv:2601.07599v4 Announce Type: replace Abstract: Single-photon avalanche diodes (SPADs) record light as a discrete stream of individual detections. The signal is stochastic. Its statistical structu

FunnelAL: Retrieve-then-Rank Active Learning for Single-Class Discovery

arXiv:2607.25276v1 Announce Type: new Abstract: We present FunnelAL, a retrieve-then-rank active learning system for single-class discovery, which adapts the multi-stage funnel architecture of industr

Game AI Not Fun? A Scoping Review and Meta-Analysis on the Differences in Enjoyment between Human and Computer Opponents

arXiv:2607.24749v1 Announce Type: cross Abstract: Although advancements in game character AI aim to enhance player engagement, evidence suggests that perceiving an opponent as artificial can diminish

@GaryMarcus OpenAI and Anthropic desperately need to raise prices. We seem to be faced with one of three choices for them: 1. Bailout 2. Ban…

Gary Marcus has argued that both OpenAI and Anthropic must increase their pricing, citing the rapid decline in token costs and competition from open‑source models. He presents a binary choice: either

safetygary-marcus--x

GAUGE: Grading Agent-Built Financial Models Without a Golden Answer

arXiv:2607.24889v1 Announce Type: cross Abstract: Financial models combine public disclosures with analyst assumptions to produce forecasts and valuations. While some components can be checked mechani

Tutorials

Gaussian Volumetric Representation for Efficient Shear-Warp Visualization

arXiv:2607.25377v1 Announce Type: new Abstract: Medical image visualization requires volumetric rendering algorithms that preserve anatomical fidelity while maintaining high rendering speeds. To addre

tutorialsarxiv-cs-cv

Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI

model-releasesarxiv-cs-lg

arXiv:2602.15021v2 Announce Type: replace-cross Abstract: Cross-survey generalization is a critical challenge in stellar spectral analysis, particularly in cases such as transferring from low- to mode

Agents

Generate Autonomous Business Insights with AI Agent and MCP Servers

Learn how Amazon Bedrock AgentCore delivers autonomous, cross-system business intelligence through configuration rather than custom code. Using pre-built MCP server connectors, fine-grained access con

agentsaws-ml-blog

Generative Distributionally Robust Optimization

arXiv:2607.24983v1 Announce Type: cross Abstract: Generative models are increasingly adopted in distributionally robust optimization (DRO), but existing approaches trade off model compatibility and ad

Generator-Aligned Representation Interfaces for Diagnostic Soft Equivariance

arXiv:2607.25988v1 Announce Type: new Abstract: Exact-equivariant architectures typically encode prescribed group actions in specialized operators, which can complicate their reuse with generic backbo

Local Ai

GeoMFD: Continual Drone-View Geo-Localization with Geometry-Aware Adapter and Margin-Field Distillation

arXiv:2607.25788v1 Announce Type: new Abstract: Existing drone-view geo-localization (DVGL) methods are mainly developed under a static training paradigm, where models are optimized for fixed environm

local-aiarxiv-cs-cv

GLIDE: Guided Layerwise Hybrid Attention for Efficient LLM Inference

arXiv:2607.24788v1 Announce Type: new Abstract: As Large Language Models scale to increasingly long contexts, the memory I/O and computational overhead of the Key-Value (KV) cache during decoding emer

GPT-5.6 Sol has been used to solve open problems in mathematics. So why was it struggling with ARC-AGI-3, a benchmark of 2D puzzle games? We…

GPT-5.6 Sol has been used to solve open problems in mathematics. So why was it struggling with ARC-AGI-3, a benchmark of 2D puzzle games? We investigated. The harness was not letting it remember what

model-releasesopenai--x

Gradient-Based Latent Decomposition Reveals Mechanisms of Feature Degradation in Weakly Supervised Mammography

arXiv:2607.24835v1 Announce Type: new Abstract: Weakly supervised hierarchical models exhibit a persistent asymmetry: coarse lesion-type features are preserved under reconstruction while fine-grained

GraphRareBench: An Auditable Graph-Evidence Benchmark for Phenotype-Driven Rare-Disease Diagnosis

arXiv:2607.24878v1 Announce Type: cross Abstract: Phenotype-driven diagnostic benchmarks usually report the rank of the reference disease, but they rarely reveal which plausible alternatives are ranke

Applications

Graphs move from niche database to enterprise knowledge layer for AI systems

As generative AI matures beyond its early experimentation phase, enterprises are converging on a shared architecture for grounding large language models in trustworthy data: the enterprise knowledge l

applicationssiliconangle

GrocLM: Grocery Category Recommendation in E-Commerce with Large Language Models

arXiv:2607.24764v1 Announce Type: new Abstract: The rapid growth of online grocery shopping requires recommendation systems that capture cyclical purchasing behavior and diverse user intents. Traditio

Grounded in Consensus, In Step With Emerging Science: A Consensus-Anchored Multi-Corpus Clinical Chatbot for Long COVID

arXiv:2607.25038v1 Announce Type: cross Abstract: Long COVID (LC) poses a challenge for clinical decision support because relevant evidence is distributed across sources with different update cycles,

Group Equivariant Diffusion for Anomaly Detection in Computational Cytology

arXiv:2607.25503v1 Announce Type: new Abstract: Computational cytology on whole-slide images is challenging because malignant cells are rare, heterogeneous, and annotated slides are scarce. Anomaly de

safetyarxiv-cs-cv

Guardians and Offenders: A Survey on Harmful Content Generation and Safety Mitigation of LLM

arXiv:2508.05775v3 Announce Type: replace Abstract: Large Language Models (LLMs) have revolutionized content creation across digital platforms, offering unprecedented capabilities in natural language

safetyarxiv-cs-cl

Guiding Posterior Exploration with Optimizer-Derived Geometry

arXiv:2607.25312v1 Announce Type: new Abstract: Sampling-based methods offer a principled approach to uncertainty quantification in Bayesian neural networks. Their practical use, however, is often cha