Search: “index”

Revitalizing Dense Material Segmentation: Stabilized Vision Transformers and the Generalization Paradox

arXiv:2605.23747v1 Announce Type: new Abstract: Material segmentation, the pixel-wise classification of physical surface properties, remains a challenging problem in computer vision, requiring physico

25 May 2026

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Research

Weierstrass Positional Encoding for Vision Transformers

DGX agent

arXiv:2605.23719v1 Announce Type: cross Abstract: Vision Transformers have achieved remarkable success in computer vision, but their common use of learnable one-dimensional positional encodings weaken

researcharxiv-cs-ai

25 May 2026

ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage

arXiv:2605.21615v1 Announce Type: cross Abstract: Existing binary corpora typically capture only one or two axes of binary variation: they either provide cross-compiler builds without a temporal axis,

Explainable AI for Data-Driven Design of High-Dimensional Predictive Studies

arXiv:2605.22243v1 Announce Type: new Abstract: Predictive modelling is important for health data analysis and data-driven clinical decision-making. However, predictive studies are challenging to desi

If you're stopping by the SF Caltrain station over Memorial Day weekend, you might catch a glimpse of our digital ads 📺 We parse (PDFs) (50…

Jerry Liu announced digital advertisements at the SF Caltrain station during Memorial Day weekend, mentioning the parsing of PDFs and a reference to '50' (likely indicating 50 PDFs or a related metric

agentsjerry-liu--x

LEMUR: Learned Multi-Vector Retrieval

arXiv:2601.21853v2 Announce Type: replace-cross Abstract: Multi-vector representations generated by late interaction models, such as ColBERT, enable superior retrieval quality compared to single-vecto

Models Can Model, But Can't Bind: Structured Grounding in Text-to-Optimization

arXiv:2605.21751v1 Announce Type: new Abstract: Text-to-optimization requires two separable capabilities: modeling -- choosing the right optimization structure -- and binding -- grounding every coeffi

Peekaboo

Peekaboo is likely a technical concept or tool discussed by Jerry Liu, co-founder of LlamaIndex, based on the X platform post. Without access to the specific tweet content, this probably covers an AI

agentsjerry-liu--x

SDPM: Survival Diffusion Probabilistic Model for Continuous-Time Survival Analysis

arXiv:2605.22776v1 Announce Type: new Abstract: Survival analysis aims to estimate a time-to-event distribution from data with censored observations. Many existing methods either impose structural ass

The Matching Principle: A Geometric Theory of Loss Functions for Nuisance-Robust Representation Learning

arXiv:2605.22800v1 Announce Type: new Abstract: Robustness, domain adaptation, photometric and occlusion invariance, compositional generalisation, temporal robustness, alignment safety, and classical

safetyarxiv-cs-lg

Tutorials

How to Build Marcus's Algebraic Mind: Algebro-Deterministic Substrate over Galois Fields

arXiv:2605.21379v2 Announce Type: cross Abstract: In The Algebraic Mind, Gary Marcus identified three components essential for any adequate cognitive architecture: operations over variables, recursive

tutorialsarxiv-cs-ai

Seizure-Semiology-Suite (S3): A Clinically Multimodal Dataset, Benchmark, and Models for Seizure Semiology Understanding

arXiv:2605.21852v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) have demonstrated remarkable proficiency in general video understanding, their capacity to interpret invo

SpaceDrive: Infusing Spatial Awareness into VLM-based Autonomous Driving

arXiv:2512.10719v2 Announce Type: replace Abstract: End-to-end autonomous driving methods built on vision language models (VLMs) have undergone rapid development driven by their universal visual under

Sub-exponential Growth Dynamics in Complex Systems: A Piecewise Power-Law Model for the Diffusion of New Words and Names

model-releasesarxiv-cs-cl

arXiv:2511.04106v5 Announce Type: replace-cross Abstract: The diffusion of ideas and language in society has conventionally been described by S-shaped models, such as the logistic curve. However, the

Build a Coding Assistant with Weaviate MCP: RAG over Code & Docs

This guide demonstrates how to build a coding assistant using Weaviate's Model Context Protocol (MCP) integration, enabling retrieval-augmented generation (RAG) capabilities over codebases and documen

model-releasesweaviate

Applications

CoarseSoundNet: Building a reliable model for ecological soundscape analysis

arXiv:2605.21143v1 Announce Type: cross Abstract: A soundscape is composed of three types of sound: biophony (sounds made by animals), geophony (natural abiotic sounds) and anthropophony (sounds made

applicationsarxiv-cs-lg

Industry

Cool release from @p0. I think this use-case (agents paying content creators for access via @mpp) will be very big. Micropayment walls haven…

Cool release from @p0. I think this use-case (agents paying content creators for access via @mpp) will be very big. Micropayment walls haven't worked (as Clay Shirky anticipated many years ago) becaus

industrysonya-huang--x

Divide et Calibra: Multiclass Local Calibration via Vector Quantization

arXiv:2605.21060v1 Announce Type: new Abstract: Accurate and well-calibrated Machine Learning (ML) models are mandatory in high-stakes settings, yet effective multiclass calibration remains challengin

Effective Model Pruning: Measure The Redundancy of Model Components

arXiv:2509.25606v3 Announce Type: replace Abstract: This article initiates the study of a basic question about model pruning. Given a vector s of importance scores assigned to model components, how ma

Multi-Head Attention as Ensemble Nadaraya-Watson Estimation: Variance Reduction, Decorrelation, and Optimal Head Diversity

arXiv:2605.20271v1 Announce Type: cross Abstract: We develop a rigorous statistical theory of multi-head attention (MHA) as an ensemble of Nadaraya-Watson (NW) kernel regression estimators. Building o

safetyarxiv-cs-lg

Physics-informed convolutional neural networks for fluid flow through porous media

arXiv:2605.20250v1 Announce Type: new Abstract: Accurate simulation of fluid flow in porous media is challenging due to complex pore-space geometries and the computational cost of solving the Navier-S

Prism: Structural Symmetry Scanning via Duality-Constrained Laplacian Projection

arXiv:2605.20245v1 Announce Type: cross Abstract: We introduce extbf{Prism}, a framework for structural symmetry diagnosis in complex networks. Given a graph Laplacian L and a duality operator P (a sy

SPARC: Spatial-Aware Path Planning via Attentive Robot Communication

arXiv:2603.02845v3 Announce Type: replace Abstract: Efficient communication is critical for decentralized Multi-Robot Path Planning (MRPP), yet existing learned communication methods treat all neighbo

researcharxiv-cs-ro

Local Ai

SpikeDet: Better Firing Patterns for Accurate and Energy-Efficient Object Detection with Spiking Neural Networks

arXiv:2501.15151v5 Announce Type: replace Abstract: Spiking Neural Networks (SNNs) are the third generation of neural networks. They have gained widespread attention in object detection due to their l

local-aiarxiv-cs-cv

The top announcements for startups from Google I/O ‘26

model-releasesgoogle-cloud-ai

Many of the world’s fastest-growing AI startups are choosing to build their future — and the world’s — on Google Cloud because of our complete and open AI stack. We embed AI into every layer of our ar

A Derandomization Framework for Structure Discovery: Applications in Neural Networks and Beyond

arXiv:2510.19382v2 Announce Type: replace-cross Abstract: Understanding the dynamics of feature learning in neural networks (NNs) remains a significant challenge. The work of (Mousavi-Hosseini et al.,

Chunking German Legal Code

model-releasesarxiv-cs-ai

arXiv:2605.19806v1 Announce Type: cross Abstract: This paper investigates chunking strategies for retrieval-augmented generation on German statutory law, using the German Civil Code as a structured be

DECOR: Auditing LLM Deception via Information Manipulation Theory

arXiv:2605.19270v1 Announce Type: new Abstract: Large language models can deceive by subtly manipulating truthful information -- omitting key facts, shifting focus, or obscuring meaning -- making such

agentsarxiv-cs-cl

Fast-BEV++: Fast by Algorithm, Deployable by Design

arXiv:2512.08237v3 Announce Type: replace Abstract: The advancement of vision-only Bird's-Eye-View (BEV) perception, a core paradigm for cost-effective autonomous driving, is hindered by the long-stan

Local Ai

GRALIS: A Unified Canonical Framework for Linear Attribution Methods via Riesz Representation

arXiv:2605.05480v2 Announce Type: replace-cross Abstract: The main XAI attribution methods for deep neural networks -- GradCAM, SHAP, LIME, Integrated Gradients -- operate on separate theoretical foun

local-aiarxiv-cs-ai

Not all uncertainty is alike: volatility, stochasticity, and exploration

arXiv:2605.19215v1 Announce Type: new Abstract: Adaptive decision-making in biological and artificial intelligence requires balancing the exploitation of known outcomes with the exploration of uncerta

Personally incredibly exciting at LangChain Labs to lead a focused, applied research effort into Continual Learning. A big prior is in treat…

Personally incredibly exciting at LangChain Labs to lead a focused, applied research effort into Continual Learning. A big prior is in treating the long horizon agent optimization problem as one that

agentsharrison-chase--x

Precision Physical Activity Prescription via Reinforcement Learning for Functional Actions

arXiv:2605.19208v1 Announce Type: cross Abstract: Physical activity (PA) plays an important role in maintaining and improving health. Daily steps have been a key PA measure that is easily accessible w

safetyarxiv-cs-lg

Sonar-TS: Search-Then-Verify Natural Language Querying for Time Series Databases

model-releasesarxiv-cs-ai

arXiv:2602.17001v2 Announce Type: replace Abstract: Natural Language Querying for Time Series Databases (NLQ4TSDB) aims to assist non-expert users retrieve meaningful events, intervals, and summaries

Swimming with Whales: Analysis of Power Imbalances in Stake-Weighted Governance

arXiv:2605.19264v1 Announce Type: new Abstract: Voting methods weighted by stakes are the fundamental governance paradigm in Proof-of-Stake (PoS) blockchains. Such a paradigm is known to be prone to p

A Conditional U-Net Pipeline with Pre- and Post-Processing for Aerial RGB-to-Thermal Image Translation

arXiv:2605.17564v1 Announce Type: new Abstract: Paired RGB-thermal data has shown significant utility across a range of applications, including image fusion, object tracking, and anomaly detection; ho

researcharxiv-cs-cv

Accelerating Redshift-Conditioned Galaxy Image Synthesis with One-step Generative Modeling

arXiv:2605.17546v1 Announce Type: cross Abstract: Understanding galaxy morphology evolution across cosmic time requires models that can generate realistic galaxy populations conditioned on redshift. I

Tutorials

AdaGraph: A Graph-Native Clustering Algorithm That Overcomes the Curse of Dimensionality and Enables Scientific Discovery

arXiv:2605.16320v1 Announce Type: cross Abstract: We present AdaGraph, a graph-native clustering algorithm born from the Structure-Centric Machine Learning (SC-ML) paradigm -- a new field of unsupervi

tutorialsarxiv-cs-ai

Artificial Adaptive Intelligence: The Missing Stage Between Narrow and General Intelligence

model-releasesarxiv-cs-ai

arXiv:2605.16844v1 Announce Type: new Abstract: Between the narrow systems we deploy and the general intelligence we speculate about lies an entire regime of machine behavior that has never received i

Better Together: Evaluating the Complementarity of Earth Embedding Models

arXiv:2605.18667v1 Announce Type: new Abstract: Earth embedding models transform Earth observation data into embeddings uniquely tied to locations on the Earth's surface. These models are typically ev

researcharxiv-cs-cv

Applications

Beyond Catalogue Counts: the Dataset Visibility Asymmetry in Low-Resource Multilingual NLP

arXiv:2605.17442v1 Announce Type: cross Abstract: Multilingual NLP often relies on dataset counts from centralized catalogues to characterize which languages are resource-rich or resource-poor. Howeve

applicationsarxiv-cs-ai

Can LLMs Refuse Questions They Do Not Know? Measuring Knowledge-Aware Refusal in Factual Tasks

arXiv:2510.01782v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) should refuse to answer questions beyond their knowledge. This capability, which we term knowledge-aware refusal,

researcharxiv-cs-ai

Causal Anomaly Detection for Lithium-Ion Battery Degradation

arXiv:2605.17334v1 Announce Type: cross Abstract: Reliable early detection of lithium-ion battery degradation requires health indicators that are physically interpretable and computable from routine c

Confidence Geometry Reveals Trace-Level Correctness in Large Language Model Reasoning

arXiv:2605.16824v1 Announce Type: cross Abstract: Large language models (LLMs) generate not only reasoning text, but also token-level confidence trajectories that record how uncertainty evolves during

researcharxiv-cs-cl

Distinguishable Deletion: Unifying Knowledge Erasure and Refusal for Large Language Model Unlearning

arXiv:2605.16776v1 Announce Type: cross Abstract: Mitigating sensitive and harmful outputs is fundamental to ensuring safe deployment of LLMs. Existing approaches typically follow two paradigms: Knowl

Echoes in Filter Bubble: Diagnosing and Curing Popularity Bias in Generative Recommenders

arXiv:2605.16825v1 Announce Type: cross Abstract: Recently, Generative Recommenders (GRs), characterized by a unified end-to-end framework, have exhibited astonishing potential in transforming the rec

GCE-MIL: Faithful and Recoverable Evidence for Multiple Instance Learning in Whole-Slide Imaging

arXiv:2605.17456v1 Announce Type: cross Abstract: Multiple instance learning (MIL) is the standard approach for whole-slide image (WSI) classification and survival prediction, where attention-based mo

researcharxiv-cs-ai

Generative 3D Gaussians with Learned Density Control

arXiv:2605.16355v1 Announce Type: cross Abstract: We present Density-Sampled Gaussians (DeG), a novel 3D representation designed to bridge the gap between adaptive rendering primitives and scalable ge

researcharxiv-cs-cv