Knowledge catalogue
arXiv:2501.08579v3 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly employed for simulating human behaviors across diverse domains. However, our position is that current
arXiv:2607.05352v1 Announce Type: cross Abstract: We introduce the first multiplayer world model for highly dynamic environments governed by complex physical interactions. Whereas single-player world
arXiv:2607.02914v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated remarkable capabilities across diverse applications, yet ensuring their simultaneous safety, helpfulness,
arXiv:2607.03663v1 Announce Type: cross Abstract: The accurate estimation of Above-Ground Biomass (AGB) in mature tropical forests remains a critical challenge in remote sensing, primarily due to the
arXiv:2607.05199v1 Announce Type: new Abstract: Physics reasoning fails structurally in small language models: an error at any step propagates forward, corrupting every inference that follows. Limited
arXiv:2601.19128v2 Announce Type: replace Abstract: In terrestrial laser scanning (TLS)-based mechanical, electrical, and plumbing (MEP) point cloud segmentation, safety-critical components such as re
arXiv:2510.17801v2 Announce Type: replace-cross Abstract: Building robots that can perceive, reason, and act in dynamic, unstructured environments remains a central challenge. Recent embodied systems
arXiv:2607.04453v1 Announce Type: cross Abstract: The assessment of planktonic standing stocks and microorganism structures is critical for understanding upper ocean biological processes. Currently, a
arXiv:2601.22652v2 Announce Type: replace-cross Abstract: Spectral gradient methods, such as the Muon optimizer, modify gradient updates by preserving directional information while discarding scale, a
This morning I released sqlite-utils 4.0, the 124th release of that project and the first major version bump since 3.0 in November 2020. In addition to some small but significant breaking changes (des
arXiv:2607.03236v1 Announce Type: new Abstract: Diffusion language models (DLLMs) generate text by iteratively denoising masked positions, exposing a trajectory of predictive distributions rather than
This study focuses on Text-to-Sounding-Video (T2SV) generation, which aims to generate a video with synchronized audio from text, with both modalities aligned to the text conditions. Despite progress
arXiv:2607.04061v1 Announce Type: cross Abstract: Distinguishing Large Language Model (LLM) generated text from human writing is a critical and difficult challenge. While LLMs are trained to write lik
arXiv:2607.02587v1 Announce Type: cross Abstract: Model cards quote trust-benchmark scores without recording when they were measured, and the same number is routinely carried across successive checkpo
arXiv:2607.03160v1 Announce Type: cross Abstract: This study examines how prompt language and translation theory-driven prompt design influence the quality of Spanish-Chinese journalistic translations
arXiv:2607.03634v1 Announce Type: new Abstract: Artificial intelligence (AI) has achieved extraordinary capabilities despite lacking many of the conceptual and scientific foundations associated with m
arXiv:2603.18482v2 Announce Type: replace Abstract: Standard decoding strategies for text generation, including top-k, nucleus sampling, and contrastive search, select tokens based on likelihood, rest
arXiv:2607.04515v1 Announce Type: new Abstract: Efik, a tonal language spoken by about 3 million second language speakers and 1.5 million native speakers in Southeastern Nigeria, remains underrepresen
arXiv:2603.22972v3 Announce Type: replace Abstract: Recent progress in image and video synthesis has inspired their use in advancing 3D scene generation. However, we observe that text-to-image and -vi
arXiv:2607.04945v1 Announce Type: new Abstract: LLMs enable the integration of external conceptual resources at inference time, creating new opportunities for detecting ideologically and historically
'Ghost memory' is a real problem with agents. You might have seen the issue where a long-running agent still confidently repeats a user fact that stopped being true weeks ago? New research names the f
I wrote about the sqlite-utils 4.0rc1 release a couple of weeks ago. Since we only have Claude Fable on our Max subscriptions for a few more days, I decided to see if it could help me get to a 4.0 sta
arXiv:2603.04390v2 Announce Type: replace Abstract: WebGIS development requires consistency, yet agentic AI often fails due to LLM context constraints, forgetting, stochasticity, instruction failure,
arXiv:2607.01418v1 Announce Type: cross Abstract: Organizations rolling out agentic command line tools like Anthropic's Claude Code and GitHub's Copilot CLI need to know who will try them, who will ke
arXiv:2607.01860v1 Announce Type: new Abstract: Recent advances in 3D Gaussian Splatting (3DGS) have enabled significant progress in dense dynamic Simultaneous Localization And Mapping (SLAM). Prevail
arXiv:2607.01690v1 Announce Type: new Abstract: Finetuning a language model on documents that are explicitly annotated as fictional results in a model that still actually believes the documents' core
arXiv:2512.10485v2 Announce Type: replace-cross Abstract: Vulnerability detection methods based on deep learning (DL) have shown strong performance on benchmark datasets, yet their real-world effectiv
arXiv:2601.01095v3 Announce Type: replace-cross Abstract: Multimodal large language models (MLLMs) have achieved impressive progress in vision-language reasoning, yet their ability to understand tempo
arXiv:2607.01883v1 Announce Type: new Abstract: Code is the medium through which large language models generate structured artifacts: charts, scientific figures, vector graphics, CAD models, 3D scenes
arXiv:2607.01829v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly proposed for aviation business operations, from documentation and training generation to customer facing a
arXiv:2607.01480v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR), along with recent selfdistillation variants such as SDPO, evaluates each rollout against a verifi
arXiv:2607.01329v1 Announce Type: cross Abstract: The geometric and topological structure of quantum cost landscapes (QCLs) governs the optimization and thus the predictive power of variational quantu
arXiv:2607.01925v1 Announce Type: new Abstract: Offline reinforcement learning (RL) holds significant potential for crowd robot navigation in human-robot coexistence applications. However, the inheren
arXiv:2607.01258v1 Announce Type: cross Abstract: The rapid advancement of Artificial Intelligence (AI) has been accompanied by significant increases in computational and environmental costs, driven b
arXiv:2607.02386v1 Announce Type: cross Abstract: While Vision Transformers have achieved remarkable success across computer vision and language applications, the geometric evolution of their internal
arXiv:2607.02371v1 Announce Type: cross Abstract: Over 285 million people worldwide live with a visual impairment, for whom everyday tasks such as avoiding obstacles, locating personal belongings, rec
arXiv:2607.01804v1 Announce Type: new Abstract: Vision-Language-Action (VLA) foundation models have recently achieved strong progress in embodied intelligence. To reduce policy-call frequency while pr
arXiv:2607.00220v1 Announce Type: cross Abstract: Artificial intelligence (AI) systems are routinely modified after deployment through retraining and changes in their environments. These transformatio
arXiv:2607.00627v1 Announce Type: new Abstract: Large language models (LLMs) are powerful pattern-completion systems, but their default operating mode - predicting the next token from a static context
arXiv:2607.00171v1 Announce Type: new Abstract: Text embeddings are standard for semantic similarity tasks, yet their evaluation remains an open challenge. Current benchmarks are static, cover only a
arXiv:2607.00272v1 Announce Type: cross Abstract: Traditional robot programming is challenging: it requires orchestrating multimodal perception, managing physical contact dynamics, and handling divers
arXiv:2607.00041v1 Announce Type: cross Abstract: Multi-agent LLM systems can decompose software-engineering work into planning, generation, validation, and repair, but a narrower systems problem rema
arXiv:2607.00605v1 Announce Type: cross Abstract: Limited Memory Language Models (LMLMs) externalize factual knowledge to a database to enable deletion-based unlearning without retraining. Existing ev
arXiv:2607.00001v1 Announce Type: new Abstract: Most approaches to AI alignment treat human preferences as fixed targets to be inferred and optimized. This assumption conflicts with extensive empirica
arXiv:2607.00009v1 Announce Type: cross Abstract: Despite the remarkable proficiency of large language models (LLMs) in basic writing assistance, their utility in creative writing is fundamentally hin
arXiv:2607.01047v1 Announce Type: new Abstract: Complexity and interpretability rarely coincide: systems rich enough for complex behaviours to emerge are usually too opaque to question, while transpar
arXiv:2607.00024v1 Announce Type: new Abstract: Cooperative aerial transport requires controllers that respect nonlinear manifold geometry, operate without centralized coordination, and respect operat
arXiv:2509.18171v4 Announce Type: replace Abstract: Federated graph learning (FGL) is a natural paradigm for social-media user graphs, where language communities, regional markets, and service boundar
arXiv:2606.18218v2 Announce Type: replace-cross Abstract: We study finite-horizon queue peaks in generalized switches, a standard stochastic-network model in which many queues share constrained servic
arXiv:2508.04064v2 Announce Type: replace-cross Abstract: Horizontal federated learning (HFL) backdoor audits often summarize model behavior through clean accuracy (CA), mean attack success rate (ASR)
arXiv:2607.00233v1 Announce Type: new Abstract: How do two agents invent a shared language from scratch? In a Lewis signaling game, a sender and receiver must coordinate on a code using only their int
arXiv:2407.10887v4 Announce Type: replace-cross Abstract: Growing concerns over the theft and misuse of Large Language Models (LLMs) underscore the need for effective fingerprinting to link a model to
LiteParse runs anywhere, including inside agent runtimes. To prove it, we built an email processing assistant using @flueai (the agentic framework by @astrodotbuild), @resend webhooks, and @tursodatab
arXiv:2607.00858v1 Announce Type: new Abstract: Contrastive pre-training has propelled video-text alignment, yet models often inherit the critical limitations of their image-text predecessors like CLI
arXiv:2607.00457v1 Announce Type: new Abstract: Embodied agents operating in the real world require multi-scale reasoning and knowledge adaptation as conditions change. We identify two challenges in a
PamStealer is a macOS infostealer disguised as the legitimate Maccy clipboard manager that uses a two-stage attack chain to silently harvest data and clipboard contents while evading detection. The ma
arXiv:2607.00248v1 Announce Type: new Abstract: We present Seed2.0, a model series that takes a meaningful step toward solving complex, real-world tasks. Our approach begins with identifying users' ge
arXiv:2607.01136v1 Announce Type: cross Abstract: Agent skills package reusable operational knowledge for Large Language Model (LLM) agents, yet as they grow in scope, they become dependency-bearing a
arXiv:2607.00063v1 Announce Type: cross Abstract: This paper studies how spectral geometry emerges in quantum learning models and how it can be diagnosed with physically grounded probes. In graph-regu
arXiv:2603.00198v2 Announce Type: replace-cross Abstract: Token reduction accelerates long-video vision--language models (VLMs), but existing methods target Transformers, where reduction is treated as