Knowledge catalogue
arXiv:2606.14668v3 Announce Type: replace Abstract: Knowledge editing systems must update selected facts while preserving nearby but irrelevant behavior. This paper studies this problem in a memory-as
When you came to Iceland in early June 2025 we had not yet started to see many of the consequences of the 2024 push to bring in people from Gaza (led by a group of women in an empathy rush). Since the
arXiv:2606.26935v1 Announce Type: new Abstract: Chain-of-thought (CoT) reasoning is widely used in language-model agents, but prior work has shown that verbalized CoT is not always faithful and may in
arXiv:2606.26987v1 Announce Type: cross Abstract: Recent work identified emotion vectors in Claude Sonnet 4.5, which are internal representations that encode emotion concepts, causally influence behav
arXiv:2606.26108v1 Announce Type: new Abstract: Larger language models consistently outperform smaller ones on reasoning benchmarks, yet the reasoning differences underlying this gap remain underexplo
Ethan Mollick compares Claude and GLM-5.2 AI models, noting that while GLM-5.2 excels in certain capabilities, Claude distinguishes itself through its self-reflective persona and other characteristics
This post likely discusses concerns about potential U.S. regulatory restrictions on open-source AI models that exceed certain capability thresholds, reflecting debate about whether advanced AI develop
This post documents a Wordle game result where the player solved puzzle #1,832 in four attempts, using the color-coded emoji system (gray for incorrect letters, yellow for correct letters in wrong pos
arXiv:2606.27374v1 Announce Type: cross Abstract: Going beyond predicting robot actions, World Action Models (WAMs) can also generate future visual observations. We build on this generative capability
arXiv:2606.26975v1 Announce Type: cross Abstract: Empirical Bayes (EB) estimators can match the first-order asymptotic risk of maximum likelihood (ML) while behaving very differently at second order:
Yeah it's a real mystery why Vance would identify with an unlikable guy whose entire life revolved around resenting an elite he felt perpetually excluded from despite credentials and success. JD Vance
You can now equip your n8n workflows with the world's best parsing/extraction over your most complex documents 📃💫 We're excited to announce that LlamaParse is now an officially verified community node
@ZeffMax Because Dario sees himself as the high priest of the AI era, the only one qualified to stand between the most advanced models and users. But this is all his fantasy, arrogance, greed, and foo
arXiv:2606.26662v1 Announce Type: cross Abstract: Graph Neural Differential Equations (GNDEs) model continuous-time graph dynamics by parameterizing Neural ODE velocity fields with Graph Neural Networ
arXiv:2606.26571v1 Announce Type: new Abstract: Zero-shot tweet-level stance detection confronts two primary challenges: (1) mitigating the context sparsity inherent in short texts, and (2) establishi
arXiv:2606.25620v1 Announce Type: cross Abstract: Robotic table tennis has emerged as a compelling benchmark for real-time robotic perception due to its fast ball dynamics and stringent timing require
arXiv:2603.19964v3 Announce Type: replace Abstract: High-resolution geometric prediction is essential for robust perception in autonomous driving, robotics, and AR/MR, but current foundation models ar
arXiv:2606.25886v1 Announce Type: cross Abstract: Existing texture datasets for tactile sensing primarily consist of sensor readings from a specific sensor interacting with available surfaces/objects
arXiv:2606.25962v1 Announce Type: new Abstract: Modern stereo-capable smartphones enable immersive XR content capture. However, hardware heterogeneity across camera modules often causes severe asymmet
arXiv:2606.13984v2 Announce Type: replace-cross Abstract: Classification and Regression Trees (CART) constitute one of the most influential paradigms in statistical learning. Although a variety of imp
arXiv:2606.26078v1 Announce Type: new Abstract: Supervised deep learning has been widely used for weld penetration state classification; however, its performance often degrades significantly under dom
arXiv:2509.15900v2 Announce Type: replace-cross Abstract: This work aims to predict blood flow with non-Newtonian viscosity in stenosed arteries using convolutional neural network (CNN) surrogate mode
arXiv:2606.25112v1 Announce Type: new Abstract: We introduce Directed Hypergraph Signal Processing (DHGSP), a unified framework that extends graph signal processing to accommodate both higher-order (p
arXiv:2602.02877v2 Announce Type: replace Abstract: This paper studies optimization for a family of problems termed extbf{compositional entropic risk minimization}, in which each data's loss is formul
arXiv:2606.25200v1 Announce Type: new Abstract: The accelerated digitalization of renewable energy smart grids through IoT sensors, AMI, and SCADA systems has significantly expanded the attack surface
arXiv:2606.24944v1 Announce Type: cross Abstract: Automated classification of acute lymphoblastic leukemia (ALL) from peripheral blood smear images has often reported near-perfect performance on the C
arXiv:2601.09117v3 Announce Type: replace-cross Abstract: Generative AI systems increasingly enable the production of highly realistic synthetic media. Civitai, a popular community-driven platform for
arXiv:2606.17775v2 Announce Type: replace-cross Abstract: Efficient processing of continuous audio streams remains a key challenge for real-time and resource-constrained systems. This paper introduces
arXiv:2602.18266v2 Announce Type: replace Abstract: Automated methods for discovering mechanistic simulator models from observational data offer a promising path toward accelerating scientific progres
arXiv:2606.25476v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated remarkable performance across natural language processing tasks, yet their deployment in high-stakes appl
arXiv:2606.25966v1 Announce Type: new Abstract: This paper investigates whether magnetic plantar sensing can be embedded directly inside the load-bearing compliant element of a low-cost semi-active pr
arXiv:2606.24981v1 Announce Type: new Abstract: We study linear TD(0) under Markovian sampling, where data are generated along a single trajectory. We provide high-probability guarantees for a plain u
arXiv:2606.24903v1 Announce Type: new Abstract: Deciding when to stop collecting labeled examples is a fundamental but undertheorized problem in applied machine learning. The saturation index S(K) = o
arXiv:2606.25380v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed across languages, but their safety behavior remains uneven across linguistic and cultural context
arXiv:2507.06457v2 Announce Type: replace Abstract: Transformers face quadratic complexity and memory issues with long sequences, prompting the adoption of linear attention mechanisms using fixed-size
arXiv:2606.26059v1 Announce Type: new Abstract: The laser welding full-penetration is of critical importance, as it constitutes one of the fundamental factors in achieving defect-free welded joints. A
arXiv:2606.24999v1 Announce Type: new Abstract: High-dimensional partial differential equations (PDEs) with unknown coefficients arise widely in scientific machine learning, including continuous-time
arXiv:2501.14622v5 Announce Type: replace Abstract: Learning efficient representations for decision-making policies is a challenge in imitation learning (IL). Current IL methods require expert demonst
arXiv:2606.25985v1 Announce Type: new Abstract: Vision-language-action (VLA) models have shown strong potential for general-purpose robot manipulation, but their inference latency remains a major obst
arXiv:2606.25068v1 Announce Type: new Abstract: Online time-series forecasters receive labels only after horizon-dependent delays, while every adaptation step spends limited compute. We study when an
arXiv:2603.22225v3 Announce Type: replace Abstract: The limited availability of dysarthric speech data makes cross-lingual detection an important but challenging problem. A key difficulty is that spee
arXiv:2505.15437v3 Announce Type: replace-cross Abstract: Reliable probability estimates by classifiers are essential in high-risk applications. In practice, however, predicted probabilities are often
arXiv:2602.12024v3 Announce Type: replace Abstract: Multi-Agent Path Finding (MAPF) is a core coordination problem for large robot fleets in automated warehouses and logistics. Existing approaches are
arXiv:2606.25003v1 Announce Type: new Abstract: Federated split learning (FSL) enables collaborative training across bandwidth-constrained IoT devices, but repeated activation and gradient exchange cr
arXiv:2606.25424v1 Announce Type: cross Abstract: Diffusion-based text-to-speech (TTS) models have achieved significant improvements in speech quality. However, modeling sharp prosodic transitions and
arXiv:2606.25111v1 Announce Type: cross Abstract: Robust multi-sensor fusion is essential for reliable autonomy in diverse and degraded environments, where sensor reliability can fluctuate rapidly. Be
arXiv:2606.25122v1 Announce Type: cross Abstract: Autonomous aerial vehicles operating in shared airspace must predict the future positions of non-cooperative obstacles to plan evasive maneuvers befor
arXiv:2606.22902v2 Announce Type: replace Abstract: Real-world users typically have access to multiple Large Language Models (LLMs) from different providers, and these LLMs often excel at distinct dom
Agentic coding forces you to design clean interfaces and document them well. An agent cannot read the implicit mental model shared by your engineering team, it can only read your API contracts and doc
arXiv:2606.25532v1 Announce Type: cross Abstract: Artificial intelligence increasingly drives automated scientific discovery, yet contemporary generalist agents lack physical grounding, frequently hal
Agentic search startup Seltz Inc. said today it has bagged 12.5 million in seed funding to build a more optimal infrastructure so that artificial intelligence agents can find their way around the web.
arXiv:2606.25358v1 Announce Type: new Abstract: Assessing financial literacy during gameplay without disrupting the learning experience remains a key challenge in serious games for education. We prese
arXiv:2509.06216v3 Announce Type: replace-cross Abstract: Agentic Software Engineering (SE 3.0) represents a new era where intelligent agents are tasked not with simple code generation, but with achie
arXiv:2606.25960v1 Announce Type: new Abstract: Large language models are turning from isolated predictors into agentic systems: they call tools, retrieve evidence, obey environment constraints, use v
arXiv:2606.24893v1 Announce Type: new Abstract: For agents to learn continuously from interaction with the world at test time, they must be able to explore effectively, acquire new world knowledge and
Agents are easy to demo locally. The hard part is shipping them inside a real app. We published a deployment cookbook for @LangChain agents: full-stack examples with streaming UI, subagents, thread hi
ah, the creative S-1 For those unfamiliar, WeWork pioneered the creative S-1 and the subsequent failure to IPO, and Sam seems to be following a comparable path. /cc @GaryMarcus https://qz.com/1685919/
AI and Liability Bruce Schneier on the recent German ruling that Google be held liable for errors introduced in their AI overviews: AI agents are agents of the person or organization that deploys them
arXiv:2606.25879v1 Announce Type: cross Abstract: Computational reproducibility remains difficult despite being central to scientific research. In this paper, we show how the international FABRIC test
arXiv:2606.25337v1 Announce Type: new Abstract: AI copilots can substantially boost human performance through shared control, but excessive assistance can induce over-reliance and skill atrophy. This