applications

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

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

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

Specialty-Specific Medical Language Model for Immune-Mediated Diseases

arXiv:2605.28838v1 Announce Type: cross Abstract: Extracting detailed clinical information from free-text medical narratives remains a practical challenge for researchers and healthcare systems. Termi

SurfFill: Completion of LiDAR Point Clouds via Gaussian Surfel Splatting

arXiv:2512.03010v2 Announce Type: replace Abstract: LiDAR-captured point clouds are often considered the gold standard in active 3D reconstruction. While their accuracy is exceptional in flat regions,

Temporal Motif-aware Graph Test-time Adaptation for OOD Blockchain Anomaly Detection

arXiv:2605.29526v1 Announce Type: cross Abstract: Ever-evolving transaction patterns have significantly hindered anomaly detection on emerging cryptocurrency blockchains due to the vast number of addr

Test Time Training for Supervised Causal Learning

arXiv:2605.30015v1 Announce Type: cross Abstract: Supervised Causal Learning (SCL) has shown promise in causal discovery by framing it as a supervised learning problem. However, it suffers from signif

The New Pro Se: Generative AI and the Surge in Federal Civil Self-Representation

arXiv:2605.29493v1 Announce Type: cross Abstract: Since public access to generative AI tools became widespread, federal civil litigation has seen a marked increase in pro se (self-represented) plainti

VLA-Pro: Cross-Task Procedural Memory Transfer for Vision-Language-Action Models

arXiv:2605.29562v1 Announce Type: cross Abstract: Vision-Language-Action~(VLA) models have shown strong potential for general-purpose robotic manipulation, yet they still struggle to generalize to uns

When Does Persona Prompting Actually Help? A Retrieval and Metric Analysis of Expert Role Injection in LLMs

arXiv:2605.29420v1 Announce Type: new Abstract: Persona prompting is widely used to steer large language models, yet its practical value remains unclear. Prior work often evaluates persona prompting u

Who Am I? History-Aware Profiles for Student Simulation in Tutoring Dialogues

arXiv:2605.30051v1 Announce Type: new Abstract: A key part of developing large language model (LLM)-powered, automated tutoring tools is student simulation, i.e., using LLMs to role-play as students,

A self-supervised learning approach to deep filter banks for texture recognition

arXiv:2605.27843v1 Announce Type: new Abstract: An important challenge in texture recognition is the limited amount of data for training frequently found in real-world applications. In computer vision

A Sheaf-Theoretic and Topological Perspective on Complex Network Modeling and Attention Mechanisms in Graph Neural Models

arXiv:2601.21207v3 Announce Type: replace-cross Abstract: Combinatorial and topological structures, such as graphs, simplicial complexes, and cell complexes, form the foundation of geometric and topol

A Wolf in Sheep's Clothing: Targeted Routing Hijacking in Federated RAG

arXiv:2605.28112v1 Announce Type: cross Abstract: Federated Retrieval-Augmented Generation (FedRAG) is attractive for privacy-sensitive applications because raw data remain local. As a result, routing

Addressing Pitfalls in Auditing Practices of Automatic Speech Recognition Technologies: A Case Study of People with Aphasia

arXiv:2506.08846v3 Announce Type: replace-cross Abstract: Automatic Speech Recognition (ASR) systems' growing use warrants robust auditing approaches to ensure equitable transcription quality, especia

AI in the Workplace: The Impact of AI on Perceived Job Decency and Meaningfulness

arXiv:2605.28680v1 Announce Type: cross Abstract: The proliferation of Artificial Intelligence (AI) in workplaces is transforming how we work. While existing research on human-AI collaboration at work

Analyzing Cancer Patients' Experiences with Embedding-based Topic Modeling and LLMs

arXiv:2601.12154v2 Announce Type: replace Abstract: This study investigates the use of neural topic modeling and LLMs to uncover meaningful themes from patient storytelling data, to offer insights tha

Architecture-driven Shift: towards a lightweight selector for capturing the trends of logit shift

arXiv:2605.27469v1 Announce Type: cross Abstract: Continual Learning (CL) is a practical paradigm to utilize power of deep pre-trained neural networks, but which pre-trained model has a better ability

AURA: Asymptotically Optimal Uncertainty-Robust Replanning Algorithm for Kinodynamic Systems

arXiv:2605.27699v1 Announce Type: new Abstract: Sampling-based motion planners offer a practical and scalable approach to kinodynamic motion planning, notably for high-dimensional, underactuated, or n

applicationsarxiv-cs-ro

BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning

arXiv:2601.18116v2 Announce Type: replace Abstract: We argue that multi-document reasoning is constrained not only by how much text a model can read, but also by how limited query-time evidence budget

Computer runs on the same secure infrastructure as the rest of Perplexity. The enterprise-grade security layer includes SAML SSO, audit logs…

applicationsperplexity--x

Computer runs on the same secure infrastructure as the rest of Perplexity. The enterprise-grade security layer includes SAML SSO, audit logs, and granular admin controls. Read more: https://www.perple

Context Features Are Cheap: Rank-Aware Decomposition for Efficient Feature Interaction in Recommender Systems

arXiv:2605.27450v1 Announce Type: cross Abstract: Modern industrial recommender systems use a deep ranking model to score N candidates against the same user and context features. Standard implementati