Knowledge catalogue
arXiv:2607.01464v1 Announce Type: new Abstract: Text scaling, the task of positioning political actors on an ideological scale, is a fundamental task in political analysis. To ease the need for manual
arXiv:2607.01940v1 Announce Type: cross Abstract: Mechanistic interpretability often relies on component-level interventions to discover how a model produces a behavior. This guides attribution, capab
arXiv:2411.16956v2 Announce Type: replace-cross Abstract: As global life expectancy increases, so does the burden of chronic diseases, yet individuals exhibit considerable variability in the rate at w
arXiv:2607.01433v1 Announce Type: new Abstract: Divergent thinking is a crucial aspect of creativity, yet large language models (LLMs) tend to consistently generate similar responses to open-ended que
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:2607.01800v1 Announce Type: cross Abstract: Large Language Models (LLMs) have recently shown promise in molecular discovery, yet a gap remains between their probabilistic nature over discrete se
arXiv:2607.02374v1 Announce Type: new Abstract: Personalization changes what a model says to a user; we show that it can also change the reasoning trajectory used to justify the response. Modern LLMs
arXiv:2607.02166v1 Announce Type: cross Abstract: The rapid advancements in using neural networks as implicit data representations have attracted significant interest in developing machine learning me
arXiv:2607.01276v1 Announce Type: cross Abstract: Embedding models are essential components of modern Information Retrieval (IR) systems, yet they are typically hidden behind APIs. Recent works have s
arXiv:2606.12623v3 Announce Type: replace-cross Abstract: Personalized medicine in acute ischemic stroke requires moving beyond average treatment effects (ATE) to individualized treatment effect (ITE)
arXiv:2607.01852v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) systems use the question-answering capabilities of Large Language Models (LLMs) to access information outside the
arXiv:2607.01548v1 Announce Type: cross Abstract: Large language models are increasingly used as open-ended search operators in evolutionary optimization. We introduce Evolutionary Feature Engineering
Exactly. I've been disseminating a similar message for years. The concentration of power in AI and the desire for control is by far the biggest danger of AI. It could lead to a few private companies a
arXiv:2607.01242v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used by end users, yet existing personalization methods relying on static profiles or text-only signals
arXiv:2607.01266v1 Announce Type: cross Abstract: We study binary classification problems whose decision sets are given by definable sets in o-minimal expansions of the real field. Motivated by cell d
arXiv:2607.01297v1 Announce Type: cross Abstract: Most existing audio classification methods suppose that each query (testing) sample belongs to a class of support (training) samples, and misrecognize
arXiv:2607.01746v1 Announce Type: new Abstract: Recurrent representations are trajectories, but representation geometry is often measured from static snapshots. We develop finite-lag operator geometry
arXiv:2607.02088v1 Announce Type: new Abstract: We propose an improved Fourier Neural Operator (FNO) for modeling two-dimensional Rayleigh-Benard convection by predicting time increments instead of fu
arXiv:2607.02199v1 Announce Type: cross Abstract: Mutual information (MI)-inspired feature learning techniques are capable of generating low-dimensional embeddings that retain nonlinear dependence str
arXiv:2607.01484v1 Announce Type: cross Abstract: We present a fully unsupervised Fast-Slow DSVDD detector for continuous State-of-Polarization monitoring on a deployed subsea cable. Trained without e
arXiv:2607.01571v1 Announce Type: new Abstract: Chain-of-thought (CoT) reasoning enables large language models (LLMs) to solve complex problems by generating intermediate reasoning steps. While much a
arXiv:2511.02496v2 Announce Type: replace Abstract: We study latent geometry as an explicit component of representation quality in data-scarce learning. For an encoder (phi), we define (Q_{eta,gamma}(
arXiv:2607.01449v1 Announce Type: new Abstract: We propose a novel hybrid neural architecture, the Geometry-aware R-Structured Kolmogorov-Arnold Network (GRS-KAN), which integrates V.L.Rvachev's R-fun
arXiv:2607.01445v1 Announce Type: cross Abstract: Malware poses a critical and ever-evolving threat, and robust and effective systems for detecting and classifying malware are of essential importance.
David Ha shares a greeting celebrating American Independence Day from Tokyo, Japan. The post likely combines holiday wishes with Ha's perspective as someone observing or living in Japan. This brief so
arXiv:2607.02020v1 Announce Type: new Abstract: Multimodal large language models must continually adapt to evolving tasks and domains, yet standard continual learning metrics mainly measure whether ol
arXiv:2512.07541v3 Announce Type: replace-cross Abstract: Inspired by graph-based methodologies, we introduce a novel graph-spanning algorithm designed to identify changes in both offline and online d
arXiv:2606.17762v2 Announce Type: replace-cross Abstract: Finite-horizon optimal-control computations repeatedly solve two-point Pontryagin boundary value problems whose conditioning can deteriorate a
arXiv:2607.01252v1 Announce Type: cross Abstract: Background: Dermatology AI has mainly focused on image-based diagnosis, while chronic disease workflows have received less attention. We surveyed Indi
arXiv:2505.15939v2 Announce Type: replace Abstract: Teleoperation systems must be aware of the human's workload during missions to maintain operator performance. Prior work employed wearable physiolog
arXiv:2607.01943v1 Announce Type: new Abstract: Quantum machine learning has recently emerged as a promising paradigm that leverages the expressive power of quantum circuits to address complex learnin
Andrej Karpathy shared a comprehensive 45-minute video demonstrating over 60 advanced 3D prompting techniques and examples using Fable, along with the actual prompts used. The content covers challengi
arXiv:2607.01279v1 Announce Type: new Abstract: Cross-subject EEG stress detection remains challenging because discriminative stress-related patterns are both subject-dependent and frequency-specific.
In retrospect... Yep One very important thing to understand about the future: the economics of AI are about to change completely. We'll soon be in a world where you can turn test-time compute into com
arXiv:2602.08542v3 Announce Type: replace-cross Abstract: Given a weighted undirected graph, a number of clusters k, and an exponent z, the goal in the (k, z)-clustering problem on graphs is to select
arXiv:2311.17633v2 Announce Type: replace-cross Abstract: Transformers have dominated empirical machine learning models of natural language processing. In this paper, we introduce basic concepts of Tr
I’ve been asked many times over why I keep posting when so many of the replies I receive are personal attacks. The answer is actually really simple. As scientists, we cannot concede to silence. If we
arXiv:2607.01880v1 Announce Type: new Abstract: Value functions are an essential component in actor-critic based deep reinforcement learning (RL). Conventionally, these functions are trained as a regr
arXiv:2510.14331v3 Announce Type: replace Abstract: We study program-learning methods that are efficient in both samples and computation. Classical learning theory suggests that when the target admits
arXiv:2602.01564v2 Announce Type: replace Abstract: We study the mean-field Langevin descent-ascent (MFL-DA), a coupled optimization dynamics on the space of probability measures for entropically regu
arXiv:2607.01921v1 Announce Type: cross Abstract: Communication systems designed for reliable data reconstruction, rather than task-oriented communication, typically rely on separate source and channe
arXiv:2607.01830v1 Announce Type: new Abstract: Reliable reward and preference signals are critical for evaluating and optimizing large language models on open-ended tasks. Rubric-based judges offer a
arXiv:2607.01336v1 Announce Type: cross Abstract: Neural Quantum States (NQS) are a remarkably expressive class of variational ansatze for quantum many-body wavefunctions, yet little is understood abo
arXiv:2607.01660v1 Announce Type: new Abstract: Hardware impairments in massive multiple-input multiple-output (MIMO) receivers introduce inter-symbol memory and inter-element coupling, severely degra
arXiv:2607.01523v1 Announce Type: cross Abstract: Recurrent memory agents extend LLMs to arbitrarily long contexts by iteratively consolidating input into a fixed-size memory window. Despite their sca
arXiv:2607.01574v1 Announce Type: new Abstract: This paper presents a novel layered planning and control framework based on multi-rate nonlinear model predictive control (MR-NMPC) that enables quadrup
arXiv:2607.01960v1 Announce Type: new Abstract: In this paper, we describe NAVER LABS Europe's submission to the instruction-following speech processing short track at IWSLT 2026. We participate again
arXiv:2607.01401v1 Announce Type: cross Abstract: INTRODUCTION: Accurate MRI-based identification of Alzheimer's disease (AD), mild cognitive impairment (MCI), and related dementias remains challengin
arXiv:2607.02423v1 Announce Type: cross Abstract: Active Few-Shot Learning (AFSL) adapts LLMs to specialized domains by identifying the most valuable unlabeled samples for annotation and use as few-sh
arXiv:2607.02404v1 Announce Type: cross Abstract: Image encoders trained with LeJEPA can deliver strong features for downstream tasks, but, like other image-level self-supervised methods, typically re
arXiv:2511.12398v2 Announce Type: replace Abstract: Deep neural networks have been widely used as universal approximators for functions with inherent physical structures, including permutation symmetr
arXiv:2607.02307v1 Announce Type: new Abstract: Several SLOG test categories explicitly involve directional distinctions (modifier position shifts, argument extraction positions), yet AM-Parser, the p
This post explores a philosophical perspective on subjective time perception, suggesting that by engaging in more diverse activities and novel experiences daily, one can psychologically expand their l
arXiv:2604.02091v2 Announce Type: replace-cross Abstract: Rerankers play a pivotal role in refining retrieval results for Retrieval-Augmented Generation. However, current reranking models are typicall
arXiv:2607.01792v1 Announce Type: new Abstract: While decoder-only LLMs excel at a vast array of natural language tasks, it suffers from an asymmetric information flow induced by causal attention: lat
arXiv:2607.01631v1 Announce Type: new Abstract: There nowadays is a myriad of approaches to real-time avoidance of fixed obstacles for unmanned surface vehicles (USVs) and, to a lesser extent, also th
arXiv:2607.01702v1 Announce Type: cross Abstract: Recently, speech classification methods have gained widespread adoption in intelligent gadgets. Current study indicates that backdoor attacks provide
arXiv:2607.01907v1 Announce Type: cross Abstract: Semi-supervised generative adversarial networks (SSL-GANs) can exploit large unlabeled datasets while retaining a classifier in the discriminator, but
arXiv:2607.02142v1 Announce Type: cross Abstract: Alzheimers disease (AD) is a brain disorder that develops slowly and mainly affects memory, thinking, language, and daily activities. It is one of the
arXiv:2607.02124v1 Announce Type: new Abstract: Conventional traction control architectures intervene only after the adhesion limit of a tire has already been breached. This paper investigates whether