Knowledge catalogue
arXiv:2605.30318v1 Announce Type: cross Abstract: Portrait photography is largely decided before the shutter opens: the subject's pose, the camera configuration, and the lighting devices must be coord
arXiv:2605.29849v1 Announce Type: cross Abstract: Machine learning (ML) is increasingly used for data-driven modeling of buildings to enable downstream tasks such as fault detection and diagnosis, and
arXiv:2605.29868v1 Announce Type: cross Abstract: Centralised biometric identity systems expose users to single points of failure, opaque verification processes, and irreversible biometric compromise.
Pritam Biswas / Reuters: Coinbase and Kalshi introduce perpetual crypto futures, marking the first time the contracts will be available to US investors via domestic, regulated exchanges — Cryptocurren
Dear Grimes, Appreciate your candor, and I understand that your subjective impression is to believe that there is something there. But a. That’s the very Eliza illusion I am pointing out. It is possib
arXiv:2605.29378v1 Announce Type: new Abstract: Natural language interfaces can simplify interaction with multi-robot systems, especially when non-expert users need to issue high-level commands. Acous
Deep Agents v0.6 makes harness profiles a first-class abstraction. Now, you can get production-grade performance from models like @Kimi_Moonshot, @Alibaba_Qwen, and @DeepSeek_ai at 20x+ lower cost tha
arXiv:2605.29353v1 Announce Type: cross Abstract: The proliferation of AI-generated synthetic media poses a critical threat to the integrity of digital evidence in legal and forensic contexts. Existin
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
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
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
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
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
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
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
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
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
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
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
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
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: 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
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-
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
arXiv:2605.29762v1 Announce Type: new Abstract: Video Motion Magnification (VMM) reveals imperceptible dynamics but often suffers from structural inconsistencies under complex geometric transformation
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
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 never make it past demo. One thesis lands hard. Here's what sepa
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
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
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,
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,
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
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
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
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
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
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
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.
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
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
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
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
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
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
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
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 likely socioeconomic conditions and locations that you woul
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
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
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
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
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
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
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
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
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
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,
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
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