Knowledge catalogue
arXiv:2608.26221v1 Announce Type: cross Abstract: As generative AI gains traction, researchers are investigating its potential to serve as proxies for humans. From undergoing cognitive psychology expe
arXiv:2608.27154v1 Announce Type: new Abstract: Vision Language Models (VLMs) have shown great success in general visual tasks, yet they still struggle to deeply understand text within images. In this
arXiv:2608.26594v1 Announce Type: new Abstract: Subseasonal-to-seasonal (S2S) precipitation forecasting has substantial financial and societal impact, yet remains challenging because of weak predictiv
arXiv:2608.27186v1 Announce Type: new Abstract: Soft actuators enable dexterous and compliant interaction, but closed-loop task-space control remains challenging due to strong nonlinearities, distribu
arXiv:2608.26235v1 Announce Type: new Abstract: Accuracy-only benchmarking of reasoning-capable large language models misses a central deployment question: when do extended thinking tokens earn their
arXiv:2608.24958v1 Announce Type: cross Abstract: An audio language model is a black box in a specific way: we see what it says, never what it works out on the way there, and chain-of-thought monitori
arXiv:2608.25370v1 Announce Type: cross Abstract: Sequential recommendation models, while powerful, have limited flexibility in responding to immediate user requests, making it difficult to adapt thei
arXiv:2608.25539v1 Announce Type: new Abstract: A plant-health score can appear precise while resting on duplicated image families, a long-tailed label space, or a runtime file that was never evaluate
arXiv:2608.25828v1 Announce Type: new Abstract: We present FlowMoDL, an unrolled neural network for highly accelerated 4D flow MRI reconstruction that directly optimizes for both anatomical magnitude
The undocumented endpoint Everyone scraping the settings page for usage stats can stop. This works with your API key (the same Bearer you use for chat completions): curl -H 'Authorization: Bearer $OLL
arXiv:2608.26083v1 Announce Type: cross Abstract: Deep neural networks often exploit spurious associations in their training data, a failure known as shortcut learning. Concept-based explainability me
arXiv:2608.26070v1 Announce Type: new Abstract: Test-time scaling uses extra test-time compute to improve performance, such as letting language models reason longer when solving a problem. As models k
When Pythian rolled out Google Cloud’s Gemini Enterprise across our 500-person company in 27 countries, the goal was simple: use our own company as a proving ground to discover how enterprise AI actua
arXiv:2608.24963v1 Announce Type: new Abstract: Published experience with neural surrogates in derivative-free optimisation is contradictory: the same family of models that cuts the evaluation count o
America is LLM-pilled. China is World-Model-Pilled. China’s booming ultra-short drama industry is being reshaped by the rapid rise of AI-generated video. In Zhengzhou, one of the country’s major produ
arXiv:2602.03702v2 Announce Type: replace-cross Abstract: Large language models are increasingly trained in continual or open-ended settings, where the total training horizon is not known in advance.
arXiv:2608.23776v1 Announce Type: cross Abstract: Understanding human skill is important for AI systems that collaborate with, coach, or assist people. Unlike typical latent variable estimation proble
arXiv:2608.24001v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for future prediction, motivating the use of multiple models as a wisdom-of-the-crowd mechanism. Howe
Qwen3.8‑Flash‑Next is a multimodal mixture‑of‑experts model with 125 B parameters that employs Gated DeltaNet (compressing historic context) and Qwen Sparse Attention (exact retrieval over full contex
Great paper on why agent leaderboard comparisons are hard to trust. It's on the hot topic of how much of an agent benchmark score actually belongs to the harness. The harness is the layer between the
arXiv:2608.23992v1 Announce Type: cross Abstract: Large language model (LLM) agents invoke external tools to retrieve and reason over information beyond pretrained knowledge. The Model Context Protoco
arXiv:2312.17535v2 Announce Type: replace Abstract: In the past two years, the outstanding performance of ChatGPT in multilingual and multitasking has led to large language models (LLMs) attracting wi
Hayden Field / The Verge: OpenAI says reward hacking, an AI alignment problem in which a model takes unintended actions to achieve a goal, was a primary driver of the Hugging Face breach — In July, an
arXiv:2608.23873v1 Announce Type: new Abstract: Everything a language model sees is tokens. The serving stack knows what each span is -- user input, tool output, instructions -- but the model must kee
arXiv:2608.24753v1 Announce Type: cross Abstract: Evaluating Retrieval-Augmented Generation (RAG) systems requires assessing not only end-to-end correctness but also how individual components interact
arXiv:2608.21747v1 Announce Type: cross Abstract: LLM-based coding agents generate complete software systems from high-level descriptions, yet little is known about how the format of architecture spec
arXiv:2608.22760v1 Announce Type: new Abstract: Byte-space Action Recognition (BAR) aims to recognize human actions directly from compressed image bitstreams without any pixel decoding. By operating e
arXiv:2608.21839v1 Announce Type: new Abstract: Reliable reward models are essential for text-to-video evaluation and alignment. However, the trade-off between evaluation accuracy and inference effici
arXiv:2608.21488v1 Announce Type: cross Abstract: While machine learning models have demonstrated strong performance in many domains, these models have shown profound vulnerabilities when they are exp
arXiv:2607.14192v3 Announce Type: replace Abstract: As recommender systems mature in the past few years, their optimization objectives have evolved from a primary focusing on short-term behavioral sig
arXiv:2511.18980v2 Announce Type: replace-cross Abstract: Foundation models (FM) are transforming artificial intelligence by enabling generalizable, data-efficient solutions across different domains f
arXiv:2608.21366v1 Announce Type: new Abstract: Driven by massive amounts of web-scale data, generative AI (GenAI) has achieved remarkable progress, enabling various applications in diverse sectors. T
arXiv:2506.13529v2 Announce Type: replace-cross Abstract: Seismic acoustic impedance plays a crucial role in lithological identification and subsurface structure interpretation. However, due to the in
arXiv:2608.22131v1 Announce Type: cross Abstract: Craniosynostosis severity analysis increasingly relies on statistical shape models (SSMs) to quantify cranial morphology, but most existing workflows
arXiv:2608.22233v1 Announce Type: cross Abstract: Test-time adaptation (TTA) aims to improve model robustness under distribution shift by adapting a source model using unlabeled test data. Although me
arXiv:2608.21114v1 Announce Type: cross Abstract: Visual world-model agents such as DreamerV3 act through a recurrent latent state rather than a single observation, which weakens frame-wise observatio
arXiv:2608.20406v1 Announce Type: new Abstract: Public health forecasts must respond to abrupt changes in surveillance data without over-extrapolating noise, reporting artifacts, or temporary trends.
arXiv:2608.21224v1 Announce Type: new Abstract: Recently, there has been a great deal of research into improving AI methods and their application. The main focus is on tracking progress, enabling tran
If you’re trying to run local LLMs on a normal laptop, an older desktop, integrated graphics, limited VRAM, or simply the hardware you already own, r/LowEndLocalAI is meant for you. The idea is simple
arXiv:2608.20953v1 Announce Type: cross Abstract: Serving large language models cheaply increasingly means shipping models that are both structurally compressed to a fraction of their parameters and q
arXiv:2608.21044v1 Announce Type: new Abstract: Class-incremental learning is commonly instantiated as a single-model paradigm, where a unified model sequentially adapts to an unbounded stream of sess
arXiv:2404.09431v3 Announce Type: replace Abstract: Pseudo-LiDAR has become a promising paradigm for monocular 3D object detection by transforming monocular images into point cloud representations tha
arXiv:2606.18847v2 Announce Type: replace Abstract: To assist humans over extended periods in real homes, embodied agents must remember user routines, world states, and past interactions. Existing lon
Heard a crazy stat the other day. Video generation represents around 70% of the share of AI token consumption in China. A combination of short form content and robotics. In China, video models are gro
AI engineers: the model absorbs the harness, and the harness transforms into an interface for human attention. > The 'attention-interface'. That's what 'The Evolution of the Agent Harness' is about. A
Live now: our AI Architects, AI Factories Track from AI Engineer World's Fair 2026. Thesis: the model is the easy part of the factory. https://www.youtube.com/watch?v=rbjWzZK2LU0&list=PLcfpQ4tk2k0VeXE
arXiv:2608.19727v1 Announce Type: cross Abstract: Watermarking is a central tool for provenance in generative models, yet its application to multivariate time series remains hindered by reliability fa
arXiv:2608.19778v1 Announce Type: cross Abstract: Pedestrian simulators need a behaviour rule for every agent, but privacy usually limits the data for setting one to aggregate statistics, namely zone-
arXiv:2608.20285v1 Announce Type: new Abstract: The causal dynamics of sleep-disordered breathing are complex and vary across patient populations, hindering the development of targeted interventions.
arXiv:2608.19297v1 Announce Type: new Abstract: While multimodal large language models (MLLMs) excel in medical applications, most of them favor static images or short-term signals. In the critical fi
arXiv:2608.20281v1 Announce Type: cross Abstract: Large language models often fail to answer questions about a bounded document collection when the source documents are not retrieved at inference time
arXiv:2603.18853v3 Announce Type: replace-cross Abstract: Autonomous aerial vehicles (AAVs) enable data collection for sixth-generation Internet-of-Things networks, but their trajectories couple nonli
arXiv:2409.06282v5 Announce Type: replace Abstract: Time series forecasting, particularly in few-shot learning scenarios, is challenging due to the limited availability of high-quality training data.
arXiv:2608.20054v1 Announce Type: new Abstract: Multi-module systems often expose every module to the full input. We test whether restricting evidence visibility changes which solutions gradient-based
arXiv:2608.18554v1 Announce Type: cross Abstract: Most LLM benchmarks rank models on their ability to automate work tasks. In practice, however, models are often used to assist other (human or LLM) ag
arXiv:2608.18084v1 Announce Type: new Abstract: Theorem proving in real-world Lean 4 projects is challenging because proofs often depend on project-specific context. While iterative refinement can use
arXiv:2508.13068v2 Announce Type: replace Abstract: Medical vision-language models still struggle to match radiologists' attention and to verbalize findings with explicit spatial grounding. We address
arXiv:2608.18881v1 Announce Type: new Abstract: Autoregressive perception models trained to localize visual entities under the open-vocabulary setting are mostly trained using Supervised fine-tuning (
arXiv:2608.18767v1 Announce Type: new Abstract: Gradient matching attacks (GMAs) in LLM split learning (SL) rely on a critical yet underexplored assumption: the gradient exposed at the split interface
Links: Preprint: https://doi.org/10.5281/zenodo.22028087 Entropic Scree Function v1.0.0 / GitHub: https://github.com/tjleestjohn/Entropic-Scree TL;DR: Standard PCA fundamentally fractures non-linear d