applications

Different models need different prompts, sometimes tools “Harness profiles” are how we do that in deepagents

applicationsharrison-chase--x

Different models need different prompts, sometimes tools “Harness profiles” are how we do that in deepagents Deep Agents v0.6 makes harness profiles a first-class abstraction. Now, you can get product

Applications

Double-Edged Sword or Sharp Tool? Designing and Evaluating Triadic LLM-Teacher Collaboration for K-12 Writing at Scale

DGX agent

arXiv:2605.30200v1 Announce Type: new Abstract: The double-edged sword of integrating Large Language Models (LLMs) requires an effective triadic collaboration mechanism among LLMs, teachers and studen

applicationsarxiv-cs-ai

29 May 2026

Dual Quaternion SE(3) Synchronization with Recovery Guarantees

arXiv:2602.00324v2 Announce Type: replace-cross Abstract: Synchronization over the special Euclidean group SE(3) aims to recover absolute poses from noisy pairwise relative transformations and is a co

Energy-Aware NECO for Single-Pass Pixel-wise Out-of-Distribution Detection in Semantic Segmentation

arXiv:2605.29773v1 Announce Type: cross Abstract: Reliable semantic segmentation for mobile robots requires both accurate dense prediction and robust uncertainty estimation under distribution shift. S

Enhancing Reinforcement Learning in 3D Environments through Semantic Segmentation: A Case Study in ViZDoom

arXiv:2511.11703v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) in 3D environments with high-dimensional sensory input poses two major challenges: (1) the high memory consumption

Evaluation of Conversational Agents: Understanding Culture, Context and Environment in Emotion Detection

arXiv:2605.30099v1 Announce Type: new Abstract: Valuable decisions and highly prioritized analysis now depend on applications such as facial biometrics, social media photo tagging, and human robots in

Evolving Features vs Evolving Entire Trees with GP for Interpretable Survival Analysis

arXiv:2605.30119v1 Announce Type: cross Abstract: Survival analysis concerns the task of predicting the time until an event occurs. Often used in the medical field, survival analysis deals with incomp

F-RNG: Feed-Forward Relightable Neural Gaussians

arXiv:2605.25975v2 Announce Type: replace-cross Abstract: Capturing relightable 3D assets from real-world objects is a widely researched problem. Several per-scene optimization-based methods, based on

Faster Molecular Dynamics with Neural Network Potentials via Distilled Multiple Time-Stepping and Non-Conservative Forces

arXiv:2602.14975v3 Announce Type: replace-cross Abstract: Following our previous work (J. Phys. Chem. Lett., 2026, 17, 5, 1288-1295), we propose the DMTS-NC approach, a distilled multi-time-step (DMTS

Follow Everything: A Leader-Following and Obstacle Avoidance Framework with Goal-Aware Adaptation

arXiv:2504.19399v4 Announce Type: replace Abstract: Robust and flexible leader-following is a critical capability for robots to integrate into human society. While existing methods struggle to general

applicationsarxiv-cs-ro

Force Sensing for Wearable Human-Robot Interfaces via Fluidic Innervation

arXiv:2602.13436v2 Announce Type: replace Abstract: Mechanically characterizing the human-machine interface is essential to understanding user behavior and optimizing wearable robot performance. This

applicationsarxiv-cs-ro

Forget Less, Generalize More: Unifying Temporal and Structural Adaptation for Dynamic Graphs

arXiv:2605.29453v1 Announce Type: cross Abstract: Representation learning on dynamic graphs requires capturing complex dependencies that evolve across both time and structure. Existing approaches typi

From GPS Points to Travel Patterns: Flexible and Semantic Trajectory Generation with LLMs

arXiv:2605.30014v1 Announce Type: new Abstract: Urban trajectories play a crucial role in modeling urban dynamics and supporting various smart city applications. However, privacy concerns restrict acc

fun fact many people don’t know:

applicationsgary-marcus--x

fun fact many people don’t know: LLMs actually produce bullshit for many reasons, and would continue to do so (though less) even they weren’t trained on bullshit. legal citation hallucinations are a n

Gaga: Group Any Gaussians via 3D-aware Memory Bank

arXiv:2404.07977v4 Announce Type: replace Abstract: We introduce Gaga, a framework that reconstructs and segments open-world 3D scenes by leveraging inconsistent 2D masks predicted by zero-shot class-

Generative Spatiotemporal Intent Sequence Recommendation via Implicit Reasoning in Amap

arXiv:2605.28888v1 Announce Type: cross Abstract: Real-world user behavior rarely consists of isolated actions; instead, it often forms intent flows governed by spatiotemporal dependencies. To provide

GeoMag: Geometric-Aware Video Motion Magnification via State Space Model

arXiv:2605.29762v1 Announce Type: new Abstract: Video Motion Magnification (VMM) reveals imperceptible dynamics but often suffers from structural inconsistencies under complex geometric transformation

GeRaF: Neural Geometry Reconstruction from Radio Frequency Signals

arXiv:2605.29097v1 Announce Type: new Abstract: GeRaF is the first method to use neural implicit learning for near-range 3D geometry reconstruction from radio frequency (RF) signals. Unlike RGB or LiD

GMOS: Grounding Moving Object Segmentation in 3D Space and Time

arXiv:2605.30352v1 Announce Type: new Abstract: Moving Object Segmentation (MOS) aims to discover, segment, and track objects that move independently of the camera. Current MOS methods, however, exhib

I watched the LangChain keynote expecting product releases. Got something better — the clearest breakdown I've heard of why most agents neve…

applicationsharrison-chase--x

I watched the LangChain keynote expecting product releases. Got something better — the clearest breakdown I've heard of why most agents never make it past demo. One thesis lands hard. Here's what sepa

In case anyone wants to improve/change/use it: https://github.com/emollick/veil-of-history

applicationsethan-mollick--x

The Veil of History is an open-source project shared by Ethan Mollick on GitHub that appears to be a tool or resource related to historical analysis or visualization, made available for public improve

It`s All About Speed: AI`s Impact on Workflow in Music Production

arXiv:2605.29931v1 Announce Type: new Abstract: In this paper, we present the results of an ethnographic study into the impact of AI and automated tools on music production workflow. Focusing specific

Looking around you: external information enhances representations for event sequences

arXiv:2502.10205v3 Announce Type: replace Abstract: Representation learning produces models in different domains, such as store purchases, client transactions, and general people's behavior. However,

LsrIF: Enhancing Logic-Structured Instruction Following of Large Language Models

arXiv:2601.06431v3 Announce Type: replace Abstract: Instruction following is critical for large language models, yet real-world instructions often involve multiple constraints with logical structures,

Measuring Real-World Prompt Injection Attacks in LLM-based Resume Screening

arXiv:2605.28999v1 Announce Type: cross Abstract: LLMs are vulnerable to prompt injection attacks. However, this vulnerability has been primarily demonstrated conceptually in academic studies or throu

Miami-based Canals, which uses AI to help distributors automate workflows across sales, customer service, and more, raised a $35M Series A led by Base10 (Chris Metinko/Axios)

Chris Metinko / Axios: Miami-based Canals, which uses AI to help distributors automate workflows across sales, customer service, and more, raised a 35M Series A led by Base10 — Canals raised a 35 mill

applicationstechmeme

Microsoft faces backlash after a blog post implied criminal referral and legal action against security researcher Nightmare Eclipse over public bug disclosures (Lorenzo Franceschi-Bicchierai/TechCrunch)

Lorenzo Franceschi-Bicchierai / TechCrunch: Microsoft faces backlash after a blog post implied criminal referral and legal action against security researcher Nightmare Eclipse over public bug disclosu

applicationstechmeme

MOO: A Multi-view Oriented Observations Dataset for Viewpoint Analysis in Cattle Re-Identification

arXiv:2603.04314v2 Announce Type: replace-cross Abstract: Animal re-identification (ReID) faces critical challenges due to viewpoint variations, particularly in Aerial-Ground (AG-ReID) settings where

Motion-guided sparse correction enables expert-quality point tracking across diverse microscopy regimes

arXiv:2605.29220v1 Announce Type: new Abstract: Tracking the dynamics of non-canonical biological systems in microscopy videos remains a persistent challenge. Both classical and learning-based tracker

Multi-Level Barriers to Generative AI Adoption Across Disciplines and Professional Roles in Higher Education

arXiv:2603.27052v2 Announce Type: replace-cross Abstract: Generative Artificial Intelligence (GenAI) is rapidly reshaping higher education, yet barriers to its adoption across different disciplines an

Obfuscation Rules for Detecting and Detoxifying Korean Toxicity

arXiv:2510.10961v3 Announce Type: replace-cross Abstract: As language models become increasingly deployed in online environments, toxicity detection and detoxification have received growing attention.

Order-Agnostic Autoregressive Modelling with Missing Data

arXiv:2605.06355v2 Announce Type: replace Abstract: Order-Agnostic autoregressive models have demonstrated strong performance in deep generative modeling, yet their use in settings with incomplete dat

P^2RAG: Efficient Privacy-Preserving RAG Service Supporting Arbitrary Top-k Retrieval

arXiv:2603.14778v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) enables large language models to use external knowledge, but outsourcing the RAG service raises privacy c

Parallel Adaptive Multi-Objective Evolutionary Learning of Discretized Bayesian Network Classifiers for Clinical Data

arXiv:2605.29058v1 Announce Type: new Abstract: Bayesian Networks (BNs) are of interest from an explainable AI viewpoint, offering transparent probabilistic models for decision support. Baymex is a re

PARCEL: Pool-Anchored Resampling with Conditioned Elastic Queries for Efficient Vision-Language Understanding

arXiv:2605.30126v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) map visual inputs into dense token sequences, imposing a quadratic computational bottleneck for inference. Elasti

PassNet: Scaling Large Language Models for Graph Compiler Pass Generation

arXiv:2605.29357v1 Announce Type: new Abstract: Modern tensor compilers such as TorchInductor deliver substantial speedups on mainstream models, yet face a systematic performance ceiling on long-tail

Persona Conditioning of Brand Recommendations in Retrieval-Augmented Commercial Chat: A Prominence-Stratified Cross-Provider Audit

arXiv:2605.30207v1 Announce Type: new Abstract: The same prompt -- 'best CRM software' -- reaches AI assistants from buyers in widely different contexts: a solo founder, an enterprise VP, a UK SMB own

Position: Text Embeddings Should Capture Implicit Semantics, Not Just Surface Meaning

arXiv:2506.08354v2 Announce Type: replace-cross Abstract: This position paper argues that text embedding research should move beyond surface meaning and embrace implicit semantics as a central modelin

Prediction-Powered Inference Across Many Tasks for AI Evaluation & Social Science Research

arXiv:2605.29249v1 Announce Type: cross Abstract: Many applications require statistically valid inference across many related tasks, while using only a handful of high-quality labels per hypothesis. I

Prompts (verbatim): assume a universal veil of ignorance and you could be born as any human who has ever lived in history, what are the most…

applicationsethan-mollick--x

Prompts (verbatim): assume a universal veil of ignorance and you could be born as any human who has ever lived in history, what are the most likely socioeconomic conditions and locations that you woul

Ray Data LLM enables 2x throughput over vLLM’s synchronous LLM engine at production-scale

Ray Data LLM, developed by Anyscale, achieves 2x higher throughput compared to vLLM's synchronous LLM engine when operating at production scale. This performance improvement likely stems from Ray Data

applicationsanyscale-ray

Reconstructing software engineering around AI is going to take work (even as the ability of AI to code increases at a rapid rate). Organizat…

applicationsethan-mollick--x

Reconstructing software engineering around AI is going to take work (even as the ability of AI to code increases at a rapid rate). Organizations are ideally spending tokens for two things: 1) building

Robust and Efficient Writer-Independent IMU-Based Handwriting Recognition

arXiv:2502.20954v3 Announce Type: replace Abstract: Handwriting recognition (HWR) using inertial measurement unit (IMU) data remains challenging due to variations in writing styles and the limited ava

SAFE-Pruner: Semantic Attention-Guided Future-Aware Token Pruning for Efficient Vision-Language-Action Manipulation

arXiv:2605.29662v1 Announce Type: new Abstract: Real-time inference of vision-language-action (VLA) models is essential for robotic control. While visual token pruning has shown strong potential for a

SAM3D-Phys: Towards Multi-Object Interactive Simulation in Real World

arXiv:2605.30239v1 Announce Type: new Abstract: This work addresses the problem of recovering complete, simulatable object geometry from reconstructed real-world scenes, enabling physics-based interac

Scalable RF Simulation in Generative 4D Worlds

arXiv:2508.12176v2 Announce Type: replace-cross Abstract: Radio Frequency (RF) sensing has emerged as a powerful, privacy-preserving alternative to vision-based methods for various perception tasks. H

Server-Proximal Aggregation for Federated Domain-Incremental Learning under Partial Participation: Task-Uniform Convergence and Backward Transfer

arXiv:2601.22274v2 Announce Type: replace Abstract: Real-world federated systems seldom operate on static data: input distributions drift while privacy rules forbid raw-data sharing. We study this set

Size Transferability of Graph Transformers with Convolutional Positional Encodings

arXiv:2602.15239v2 Announce Type: replace Abstract: Transformers have achieved remarkable success across domains, motivating the rise of Graph Transformers (GTs) as attention-based architectures for g