Knowledge catalogue
arXiv:2609.16427v1 Announce Type: new Abstract: This paper presents a Belarusian-specific data-cleaning pipeline and fine-tuning for English-Belarusian machine translation. Our cleaning pipeline disti
arXiv:2609.16930v1 Announce Type: cross Abstract: Deep Limit Order Book forecasting models capture nonlinear market dynamics, but their ability to quantify the effects of counterfactual order book mes
arXiv:2510.09619v2 Announce Type: replace-cross Abstract: [Corrected v2: an audit found that the score, threshold, and latency descriptions below are not what the shared codebase implements, and that
arXiv:2508.19003v2 Announce Type: replace-cross Abstract: Roof plane segmentation is one of the key procedures for reconstructing three-dimensional (3D) building models at levels of detail (LoD) 2 and
arXiv:2602.06652v2 Announce Type: replace Abstract: The robustness of Vision Language Models (VLMs) is commonly assessed through output-level invariance, implicitly assuming that stable predictions re
arXiv:2609.17287v1 Announce Type: new Abstract: In flow matching (FM), a velocity model v_{heta} is trained using a predefined path g_t that connects data and noise samples (e.g., g_t(x_0, x_1) = (1 -
arXiv:2609.17076v1 Announce Type: new Abstract: Few-shot audio classifiers may rely on foreground-background co-occurrences and fail when those correlations shift. On SpurAudio, the resulting represen
arXiv:2601.10511v2 Announce Type: replace-cross Abstract: Model counting of Disjunctive Normal Form (DNF) formulas is a critical problem in applications such as probabilistic inference and network rel
arXiv:2609.16282v1 Announce Type: new Abstract: Learning-based surrogates for AC optimal power flow (ACOPF) promise large speedups over classical solvers, but their operational value depends on physic
arXiv:2609.17091v1 Announce Type: new Abstract: Multi-target regression requires a model to simultaneously predict several related outputs. Conformal prediction provides distribution-free, finite-samp
arXiv:2609.16071v1 Announce Type: cross Abstract: Cross-machine deployment of industrial world models requires transfer across changes in dynamics, sensing interfaces, sampling regimes, and control un
arXiv:2609.16279v1 Announce Type: cross Abstract: Emerging physical AI systems require low-latency, task-oriented video communication over unreliable channels. We propose a semantic-aware multi-level
arXiv:2609.17100v1 Announce Type: new Abstract: Liver cancer is a complex disease responsible for a high number of deaths across the globe each year, making automated solutions for liver cancer classi
arXiv:2609.17109v1 Announce Type: new Abstract: A common small-model deployment runs one shared backbone with several LoRA specialists that answer over the same context. Serving them naively re-prefil
arXiv:2512.18021v4 Announce Type: replace-cross Abstract: In trapped-ion quantum computers, qubits must be shuttled between segments to interact. The routing logic that schedules these movements is wr
arXiv:2609.15993v1 Announce Type: new Abstract: Automatic Text Summarization (ATS) in Natural Language Processing has been an important task in Information Retrieval. It compresses a document to creat
arXiv:2601.09050v2 Announce Type: replace Abstract: Tonal low-resource languages are widely spoken but remain underserved by modern speech technologies. A central challenge is learning speech represen
arXiv:2609.16804v1 Announce Type: cross Abstract: Time-series foundation models have demonstrated strong cross-domain transfer, yet their common architectural assumptions remain poorly aligned with we
arXiv:2609.16275v1 Announce Type: new Abstract: Charismatic speech is shaped by language and speaking style, yet their relative contribution in bilingual public speaking remains unclear. We analyzed s
arXiv:2609.16274v1 Announce Type: new Abstract: Speech rhythm helps structure persuasive speech, but most empirical work examines monolingual English. This study asks how politicians organize timing w
arXiv:2609.16871v1 Announce Type: new Abstract: Earth observation is inherently dynamic, yet temporal information in many foundation models is learned through reconstruction, invariance, or retrospect
arXiv:2603.02055v2 Announce Type: replace Abstract: Personal AI assistants are changing how individuals use advice. We study how an advisor should design its recommendation in anticipation of stochast
arXiv:2609.16612v1 Announce Type: cross Abstract: Vocal repertoires can differ in acoustic-event type accumulation and temporal organization, yet direct comparison is difficult because corpora use dif
arXiv:2607.11233v2 Announce Type: replace Abstract: Virtual try-on (VTON) is a bi-conditional image generation problem that requires not only accurate person preservation but also faithful garment def
arXiv:2609.16089v1 Announce Type: new Abstract: Structured spatial data require quantum encodings that preserve geometric relations, expose measurable observables, and remain implementable on finite-d
arXiv:2609.16099v1 Announce Type: new Abstract: Robust aggregation methods for federated learning quietly rest on a fragile assumption: that whoever shows up in a given round is a fair sample of the f
arXiv:2609.17240v1 Announce Type: new Abstract: We present a palm-scale (65 mm, 34 g) swim-and-breach robot platform. Two vertically stacked propellers provide both propulsion and differential-thrust
arXiv:2609.17004v1 Announce Type: new Abstract: Frozen vision-language models (VLMs) remain unreliable on fine-grained left-right claims, and raw claim likelihoods need not reliably rank verification
arXiv:2512.05126v2 Announce Type: replace-cross Abstract: Automatic video dubbing aims to generate high-fidelity speech that is temporally aligned with visual content. However, existing methods still
arXiv:2609.16967v1 Announce Type: new Abstract: Ensuring that multilingual language models generate coherent text in a specific target language is a major issue in multilingual language modeling. We d
arXiv:2609.16870v1 Announce Type: new Abstract: Video compression aims to minimize reconstruction distor tion under a constrained bit rate. Existing video implicit neural representations (INRs) often
arXiv:2609.16889v1 Announce Type: new Abstract: Recent advances in angiographic imaging have enabled longitudinal visualization of the microvasculature. Image processing pipelines based on vessel grap
arXiv:2609.16258v1 Announce Type: new Abstract: As artificial intelligence's capabilities improve, it is increasingly viewed as a general scientific method. But how true are these claims? Does AI outp
arXiv:2602.02132v2 Announce Type: replace Abstract: Prior work argues that refusal in large language models is mediated by a single direction, enabling steering and abliteration. We show that this acc
arXiv:2609.16796v1 Announce Type: cross Abstract: Time-warping estimation is a fundamental problem in signal processing with applications in bioacoustics, radar, and biomedical analysis. This paper in
Today everyone is talking about Recursive Self-Improvement (RSI). In 1987, when compute was 100,000,000 x more expensive, I published the 1st concrete RSI algorithms. Now compute is cheap, and RSI is
arXiv:2609.17260v1 Announce Type: new Abstract: Cyber-Physical Systems (CPS) operate through a continuous sense-compute-act loop within an open context environment, making it impossible to anticipate
arXiv:2609.17427v1 Announce Type: cross Abstract: Real-time multi-object tracking systems remain highly vulnerable to full and long-term occlusion, where targets temporarily or completely disappear fr
arXiv:2512.02323v2 Announce Type: replace Abstract: Efficient sampling from Boltzmann distributions over discrete variables is a fundamental operation in a wide range of applications. While fast non-M
Discrete flow matching generates text by iteratively transforming noise tokens into coherent language, but may require hundreds of forward passes. Distillation uses the multi-step trajectory to train
arXiv:2609.16368v1 Announce Type: cross Abstract: Vision-language models (VLMs) can generate routes directly from aerial imagery for off-road navigation, but their predictions provide no indication of
arXiv:2609.16738v1 Announce Type: cross Abstract: Power Flow (PF), Optimal Power Flow (OPF), and State Estimation (SE) are fundamental problems in power system analysis, but solving them is computatio
arXiv:2609.16927v1 Announce Type: cross Abstract: Subliminal learning is a phenomenon in which a distillation dataset transmits traits from the teacher model that are not legibly encoded in the datase
arXiv:2609.16014v1 Announce Type: new Abstract: This paper addresses the challenge of generating high-quality academic charts that match the visual standards of human-authored papers. While existing A
arXiv:2609.16722v1 Announce Type: new Abstract: Scaling Multimodal Large Language Models (MLLMs) to long-form video understanding is bottlenecked by the explosion of visual tokens, which saturates con
arXiv:2609.16565v1 Announce Type: cross Abstract: Answerability on Visual Question Answering is a novel and attractive task to predict answerable scores between images and questions in multi-modal dat
arXiv:2609.17327v1 Announce Type: cross Abstract: This paper describes our submission to the SHROOM-Visions shared task on detecting and classifying hallucinated character spans in vision-language mod
arXiv:2609.17515v1 Announce Type: new Abstract: Pruning can reduce the deployment cost of large language models (LLMs), but its impact on context-grounded tool calling remains poorly understood. We sy
arXiv:2609.17516v1 Announce Type: cross Abstract: Large language models can produce fluent answers when their factual support is weak. This paper introduces Chain-of-Self-Questioning (CoSQ), a prompt-
arXiv:2609.16391v1 Announce Type: cross Abstract: Weight-only post-training quantization is the cheapest way to shrink a retrieval embedder, and the received advice for applying it -- protect the embe
arXiv:2609.16551v1 Announce Type: new Abstract: Self-supervised learning (SSL) can reduce the need for labelled medical images, but the choice of pretext objective remains unclear for lung ultrasound
arXiv:2609.17310v1 Announce Type: new Abstract: This study investigates the zero-shot ability of large language models (LLMs) to identify and classify hidden narratives in social messages. Our researc
arXiv:2609.15241v1 Announce Type: new Abstract: Dynamic-vision-sensor (DVS) cameras generate events on a per-pixel basis with a mus-level temporal resolution, calling for new algorithm-hardware co-des
arXiv:2609.13255v1 Announce Type: new Abstract: Facial state analysis plays a crucial role in understanding human expressions, psychological modeling, and human computer interaction. Traditional unimo
arXiv:2404.00727v3 Announce Type: replace Abstract: All state-of-the-art coreference resolution (CR) models involve finetuning a pretrained language model. Whether the superior performance of one CR m
arXiv:2609.13168v1 Announce Type: cross Abstract: Speech AI, any AI system that recognizes, transforms, or generates speech, is built and evaluated across two communities with only a small overlap: te
arXiv:2609.14419v1 Announce Type: cross Abstract: Person re-identification (ReID) is essential for multi-camera surveillance and tracking, yet remains difficult due to viewpoint and illumination chang
arXiv:2609.13481v1 Announce Type: new Abstract: Large language models have made abstractive summarization remarkably fluent, but generated summaries can hallucinate facts, posing serious risks in biom
arXiv:2609.14438v1 Announce Type: cross Abstract: When the same question is asked of multiple AI advisers, as in self-consistency and LLM-as-a-judge panels, Condorcet's jury theorem predicts that addi
arXiv:2609.13170v1 Announce Type: cross Abstract: Blockchain-enabled Federated Learning (FL) marketplaces enable collaborative model training among mutually distrustful participants through smart cont