Knowledge catalogue
arXiv:2609.37590v1 Announce Type: new Abstract: LLM agents accumulate interaction histories that grow linearly with task length, causing quadratic inference cost scaling and performance degradation fr
arXiv:2609.37733v1 Announce Type: cross Abstract: Second-quantized neural-network quantum states have achieved accurate molecular energies, but extending them across molecular geometries requires a sh
arXiv:2609.36056v1 Announce Type: new Abstract: In urban low-altitude flight, buildings reshape ambient wind into spatially varying 3D flow, making unmanned aerial vehicle (UAV) energy depend on local
arXiv:2609.37855v1 Announce Type: cross Abstract: Hand anthropometry supports protective-glove design, but existing measurement methods often require trained operators, specialized hardware, or manual
arXiv:2512.15684v2 Announce Type: replace-cross Abstract: Partial Least Squares (PLS) is a widely used method for data integration, designed to extract latent components shared across paired high-dime
arXiv:2609.36896v1 Announce Type: new Abstract: Recent advances in generative planning have made trajectory inpainting a promising approach to offline goal-conditioned reinforcement learning. However,
arXiv:2609.36672v2 Announce Type: new Abstract: Efficient exploration in high-dimensional decision spaces remains a central challenge for decision-making systems. Humans, in contrast, can navigate lar
arXiv:2609.35845v1 Announce Type: new Abstract: Macroeconomic productivity metrics, such as Total Factor Productivity, register technological breakthroughs with multi-year reporting lags due to admini
arXiv:2609.36012v1 Announce Type: new Abstract: General-purpose robots must infer what a new task requires and translate that understanding into appropriate physical action. In-context learning (ICL)
arXiv:2609.37603v1 Announce Type: cross Abstract: A common safeguard for a data pipeline is redundant computation: derive each published number by two routes built on different technology and refuse t
arXiv:2609.37220v1 Announce Type: new Abstract: Exploring high-order correlations and long-range dependencies in brain networks holds significant value for both neuroscience research and clinical diag
arXiv:2609.37849v1 Announce Type: cross Abstract: Scientific software is increasingly required to process larger datasets while maintaining acceptable execution times. Software optimization traditiona
arXiv:2609.26550v3 Announce Type: replace Abstract: LLM-as-a-judge scales evaluation, but reasoning judges are slow and costly. We study JEV-as-a-Judge: evaluation with JEV, a decision-only judge that
arXiv:2609.36371v1 Announce Type: cross Abstract: Test-time scaling improves software engineering agents by generating multiple candidate trajectories and selecting the best one. Verifying and selecti
arXiv:2609.36932v1 Announce Type: new Abstract: Recently, Group Relative Policy Optimization (GRPO) and its variants have been developed for policy optimization and demonstrated notable performance ga
arXiv:2609.36882v1 Announce Type: new Abstract: Localizing AI-edited regions is essential for interpretable forensic analysis, but remains challenging due to subtle and spatially distributed artifacts
arXiv:2609.37937v1 Announce Type: new Abstract: How much of an image does a detector need to see? Small RGB regions can retain useful evidence of image synthesis even when they reveal little of the fu
arXiv:2609.37408v1 Announce Type: new Abstract: Narrative extraction allows us to identify online hate narratives, supporting the construction of rigorous detection systems. Existing computational app
arXiv:2609.36426v1 Announce Type: cross Abstract: A detector pretrained on a broad corpus is fine-tuned on a narrow domain, its in-domain accuracy improves, and it ships. We ask what happens meanwhile
arXiv:2609.37819v1 Announce Type: cross Abstract: Electronic invoices are replacing paper invoices worldwide, but today's centralized architectures leave three problems unsolved on the consumption sid
arXiv:2609.36130v1 Announce Type: new Abstract: Long-running LLM agents compress past interactions into persistent memories that may be reused as premises for later tasks. This creates a distinct deri
arXiv:2609.36679v1 Announce Type: new Abstract: Machine learning engineering (MLE) agents have made substantial progress, but learning through ML experimentation remains costly in time and computation
arXiv:2506.01004v3 Announce Type: replace-cross Abstract: Unlike traditional video editing or inpainting, video semantic mixing fuses a reference concept with a moving target entity to produce a hybri
arXiv:2309.15670v3 Announce Type: replace-cross Abstract: In recent years, Sentiment Analysis (SA) and Emotion Recognition (ER) have been increasingly popular in the Bangla language, which is the seve
arXiv:2609.36756v1 Announce Type: cross Abstract: One-dimensional (1D) variable-length visual tokenizers enable adaptive compression by varying the number of tokens, allowing downstream autoregressive
arXiv:2609.36620v1 Announce Type: new Abstract: Structural reasoning, the ability to recognize and make inferences over the relational structure between objects and concepts, is a hallmark of human co
arXiv:2609.36375v1 Announce Type: new Abstract: Continual learning is usually studied through mechanisms that preserve old knowledge. We develop Successional Learning Theory (SLT), a mesoscopic accoun
arXiv:2609.37331v1 Announce Type: new Abstract: Balancing performance trade-offs on long-tailed data distributions remains a long-standing challenge in visual recognition. Existing methods mainly impr
Taiwan-based neocloud GMI Cloud Inc. wants to capitalize on what it says is an “unprecedented” demand for artificial intelligence computing power after raising a massive 663 million in funding from tw
arXiv:2609.36442v1 Announce Type: cross Abstract: Continual learning enables vision systems to adapt to ever-changing data distributions. Despite significant advances, existing approaches fail to capt
OpenAI launched Dots at DevDay. My thoughts. First, the good. Always-on is really really really what the market needed. It's why I find myself reaching for Instinct so often. I don’t have to think abo
OpenAI's New Agent Stack: Superhuman Computer Use, Dots, Decisions API, UltraFast, & the AI Cloud https://www.latent.space/p/devday-2026 @OpenAI’s @AriX and @nikunjhanda explain why Computer Use is al
arXiv:2609.38073v1 Announce Type: cross Abstract: We study exact learning with membership queries for concept classes mathcal Csubseteq{0,1}^N, focusing on the relationships among their deterministic,
arXiv:2609.36263v1 Announce Type: cross Abstract: Existing multimodal scaling laws fit multimodality terms empirically after testing and never vary how much data is multimodally paired at fixed data b
arXiv:2609.37001v1 Announce Type: cross Abstract: Diffusion Transformers (DiTs) enable high-quality video generation but suffer from substantial inference latency, primarily attributable to the comput
arXiv:2609.37350v1 Announce Type: new Abstract: The development of AI systems for tumor-specific applications is limited by the scarcity of labeled data. Synthetic tumor inpainting offers a promising
arXiv:2602.03915v2 Announce Type: replace-cross Abstract: Tokens are discrete representations that allow modern deep learning to scale by transforming high-dimensional data into sequences that can be
arXiv:2609.36193v1 Announce Type: new Abstract: Learning from scientific measurements often requires aligning modalities with different spatial support and resolution. Subsurface characterization is a
arXiv:2609.37022v1 Announce Type: new Abstract: Efficient patient flow coordination across autonomous hospital departments is critical for mitigating overcrowding and balancing resource utilization. W
arXiv:2609.37784v1 Announce Type: new Abstract: Satellite observations, precomputed embeddings, and map products describe the same evolving Earth, yet are stored as independent, petabyte-scale data pr
arXiv:2609.36543v1 Announce Type: new Abstract: Partial observability remains a fundamental challenge in robotic navigation, where limited sensor coverage and occlusions leave large portions of the en
arXiv:2503.03791v1 Announce Type: cross Abstract: Understanding how individual traits influence team performance is valuable, but these traits are not always directly observable. Prior research has in
arXiv:2609.37717v1 Announce Type: cross Abstract: Decoder-only transformers are trained only through a terminal next-token prediction loss, yet this loss constrains every intermediate hidden state thr
arXiv:2609.37789v1 Announce Type: cross Abstract: Self-supervised learning (SSL) by predicting in latent space, without generating the input data itself, learns highly abstract, useful representations
arXiv:2609.36872v1 Announce Type: new Abstract: Flow-matching policies can represent complex robot behaviors but remain susceptible to local errors under distribution shift at deployment. Many reinfor
arXiv:2609.37529v1 Announce Type: new Abstract: Pretrained denoisers provide a powerful way to incorporate image priors into restoration algorithms. Plug-and-Play and RED approaches exploit fixed-nois
arXiv:2609.35937v1 Announce Type: cross Abstract: While prior work has documented privacy failures in LLM agents, it remains unclear how the presentation of privacy guidance influences their choice of
arXiv:2609.37681v1 Announce Type: new Abstract: Long-horizon robotic tasks are vulnerable to unexpected environmental changes that can render planned actions ineffective or unsafe. To address this, ro
The chief executives of five tech giants have signed a voluntary artificial intelligence safety accord backed by the White House. U.S. President Donald Trump posted the document on Truth Social late T
arXiv:2507.21135v2 Announce Type: replace Abstract: We demonstrate how Quantum Cognition Machine Learning (QCML) encodes data as quantum geometry. In QCML, features of the data are represented by lear
arXiv:2609.36902v1 Announce Type: new Abstract: Existing multimodal fake news detection methods often introduce external information to assist detection. However, most of them rely on entity-level ret
arXiv:2609.37089v1 Announce Type: new Abstract: Real-world videos provide rich demonstrations of manipulation, but turning them into reusable robot skills requires visually aligned environments, execu
arXiv:2609.37831v1 Announce Type: new Abstract: Real-time diffusion-based video super-resolution (VSR) is in high demand for online streaming, yet stringent latency requirements often compromise gener
Ollama’s new limits and max plans are worrying me, so I’ve been going harder on my harness. (Thanks to everyone who’s signed up for the waitlist so far.) Wanted to share how my v1.10.0 will dramatical
arXiv:2609.37311v1 Announce Type: new Abstract: Recent Recommendation Agents (RecAgents) offer a promising alternative by shifting recommendation to an active, user-side paradigm, where generative age
arXiv:2609.36850v1 Announce Type: new Abstract: Generative content is increasingly entering the production and dissemination of news, transforming fake news from manually fabricated or simply manipula
arXiv:2609.38024v1 Announce Type: new Abstract: An agent skill is a reusable, actionable natural-language artifact that guides an agent to perform a task effectively under a given harness. Recent stud
arXiv:2609.36866v1 Announce Type: new Abstract: Inter-modality MRI translation aims to synthesize missing MRI modalities from available acquisitions, reducing the need for additional scanning while pr
arXiv:2609.35790v1 Announce Type: cross Abstract: While neural theorem provers have achieved impressive milestones in formal mathematics, they largely operate on the assumption that faithful Lean 4 fo
arXiv:2609.36939v1 Announce Type: new Abstract: GUI agents automate tasks on digital devices by grounding language instructions in visual interfaces. Existing group-relative reinforcement learning imp