Knowledge catalogue
arXiv:2609.31360v1 Announce Type: new Abstract: Inference in LLMs is conventionally a fixed-depth, fixed-order forward pass through every layer, regardless of how difficult the input is. The human bra
arXiv:2609.31351v1 Announce Type: new Abstract: Time-series carry structure simultaneously at multiple scales (fine-grained variation, mid-range motifs, and global properties) and downstream tasks ope
arXiv:2609.31505v1 Announce Type: new Abstract: Despite the growing capabilities of large language models (LLMs), prompt design remains largely heuristic and ad hoc. This project will explore extit{pr
arXiv:2606.06393v2 Announce Type: replace Abstract: Proper scoring rules provide a rigorous theoretical basis for the training and evaluation of probabilistic forecasts. In survival analysis, such for
arXiv:2609.30555v1 Announce Type: cross Abstract: We study proportional representation in temporal voting, where one candidate is selected in each round. While prior work has focused on approval ballo
arXiv:2602.06042v2 Announce Type: replace-cross Abstract: The Moore-Penrose Pseudo-inverse (PInv) serves as the fundamental solution for linear systems. In this paper, we propose a natural generalizat
arXiv:2609.31235v1 Announce Type: new Abstract: Artificial neural networks (ANNs) usually represent neural transmission with fixed trainable weights during a training batch, which omits short-term cha
arXiv:2609.31008v1 Announce Type: new Abstract: Quadruped robots typically rely on depth cameras and LiDAR sensors to map their local environment. However, these sensors have limited close-range cover
arXiv:2609.30820v1 Announce Type: cross Abstract: Looped transformers reuse weights across recurrence steps, making low-bit quantization especially attractive. We identify two distinct failure modes o
arXiv:2602.00158v3 Announce Type: replace-cross Abstract: Probing studies what information is encoded in a frozen LLM's layer representations by training a lightweight predictor on top of them. Beyond
arXiv:2609.30460v1 Announce Type: new Abstract: High-level robotic supervisors coordinate capabilities whose reported outcomes determine the robot's next action. Reactive synthesis can generate such s
arXiv:2609.31374v1 Announce Type: cross Abstract: Closed-loop driving simulation requires rendered observations to remain reliable as the ego vehicle and surrounding actors move beyond their recorded
arXiv:2609.31160v1 Announce Type: cross Abstract: Vessel segmentation in medical images is essential for many clinical tasks, ranging from diagnosis to treatment planning. However, it remains challeng
arXiv:2609.30470v1 Announce Type: new Abstract: Multimodal Sentiment Analysis (MSA) aims to infer human emotions from multiple modalities such as text, audio, and vision. In practice, inputs are often
arXiv:2609.30865v1 Announce Type: new Abstract: COLMAP-free 3D Gaussian Splatting (3DGS) bypasses computationally expensive structure-from-motion (SfM) pipelines, yet progressive camera pose tracking
arXiv:2609.31191v1 Announce Type: cross Abstract: Data quality research has usually treated data as an input that is stored, processed, and validated. In AI-driven software-intensive systems, data als
arXiv:2609.30885v1 Announce Type: cross Abstract: We introduce a framework for retraction-based convex optimization on Riemannian manifolds, which includes a notion of retraction-specific convex sets
arXiv:2609.31201v1 Announce Type: new Abstract: Scaling studies typically represent training data by a single count of samples. For hierarchically and spatially structured data, however, the same numb
arXiv:2609.30477v1 Announce Type: cross Abstract: Exact Euclidean (K)-means partitions (n) observations into (K) unlabelled clusters, but the unrestricted search is generally exponential. We use data-
arXiv:2609.31466v1 Announce Type: new Abstract: Graph neural networks (GNNs) rely on message passing over graph edges, making their computational and memory costs strongly dependent on graph density.
arXiv:2603.02843v2 Announce Type: replace Abstract: Generalisation across image scales remains a fundamental challenge for deep networks, which often fail to handle images at scales not seen during tr
arXiv:2609.30739v1 Announce Type: new Abstract: Multilingual text-vision embedding models are essential for cross-lingual image-text retrieval, but Southeast Asian languages remain poorly supported du
arXiv:2609.30281v1 Announce Type: new Abstract: We present a focused and reproducible study of multi-horizon forecasting on the Lomnicky Stit neutron monitor (LMKS) time series. Our evaluation suite c
arXiv:2609.30936v1 Announce Type: new Abstract: Improving reasoning abilities in Large Language Models (LLMs) requires high-quality data that exposes difficult decisions, competing alternatives, and t
arXiv:2609.30753v1 Announce Type: cross Abstract: A punch is a ballistic, full-body action driven by a kinetic chain running from the legs through the trunk to the arm, where a small sequencing error
arXiv:2609.30294v1 Announce Type: cross Abstract: Scientific presentations are more than summaries of research papers. They need to present the work in a coherent sequence, explain the main ideas clea
arXiv:2511.19422v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have shown impressive capabilities in code generation across many programming languages but even state-of-the-art
arXiv:2609.31403v1 Announce Type: cross Abstract: Vision-language models (VLMs), despite their success in optical character recognition (OCR) tasks, are vulnerable to typographic attacks and have a fr
arXiv:2609.30941v1 Announce Type: cross Abstract: Single-image novel view synthesis (NVS) enables photorealistic rendering of un- observed viewpoints from a single input. Practical NVS systems require
arXiv:2609.31164v1 Announce Type: cross Abstract: Recommender systems engineer serendipity to foster active exploration and break predictable consumption cycles. The problem with existing offline beyo
arXiv:2603.20896v2 Announce Type: replace-cross Abstract: Hyper-Connections (HC) extend residual connections into multiple streams, employing residual matrices for cross-stream mixing to enrich model
arXiv:2509.14952v3 Announce Type: replace Abstract: This paper considers the smooth bilevel optimization in which the lower-level problem is strongly convex and the upper-level problem is possibly non
arXiv:2609.31571v1 Announce Type: new Abstract: Many LLM training and inference methods, including RL and test-time scaling, depend on repeated sampling, but benefit only when the responses meaningful
arXiv:2509.25685v3 Announce Type: replace Abstract: We propose Structured-Diffuser, a diffusion planner that embeds task and motion structure directly into the noise model. Unlike standard diffusion-b
arXiv:2609.30784v1 Announce Type: cross Abstract: This paper proposes an architecture for equipping large language models (LLMs) with audio-understanding capabilities without fine-tuning their weights
arXiv:2609.30506v1 Announce Type: new Abstract: Humanoid hands require tactile feedback across the whole finger, not just the fingertip, to grasp and manipulate objects properly. Vision and propriocep
arXiv:2609.30984v1 Announce Type: new Abstract: Text-to-speech needs written text in spoken form, and speech recognition output needs the reverse. For Khmer, neither direction has a maintained open-so
arXiv:2512.23619v3 Announce Type: replace Abstract: We investigate the topological structure of the optimal actuation landscape for fully-actuated N-rotor aerial vehicles. By formulating the design pr
arXiv:2609.31098v1 Announce Type: new Abstract: We introduce effective depth (Deff), a scalar diagnostic that treats the layer-wise residual stream of a transformer as a discrete-time process, measure
arXiv:2609.30358v1 Announce Type: new Abstract: Nanodrones require accurate, real-time state estimation under severe sensing and computational constraints. We present TinyCVIO, a visual-inertial odome
arXiv:2601.01842v2 Announce Type: replace Abstract: Dictionary definitions are an essential resource for learning word senses, but manually creating them is costly. We thus study dictionary definition
arXiv:2609.30957v1 Announce Type: new Abstract: The empirical success of pretraining large language models has inspired a deeper investigation into the underlying loss landscapes and the optimization
arXiv:2609.31376v1 Announce Type: cross Abstract: Congenital heart disease (CHD) is the most common birth defect, yet a large fraction of cases remain undetected on prenatal ultrasound, in part becaus
arXiv:2609.30924v1 Announce Type: new Abstract: Accurate and efficient pronunciation transcription is essential for preparing text-to-speech training data at scale. Existing approaches have different
arXiv:2609.30894v1 Announce Type: new Abstract: We introduce Acacia, a graph foundation model, trained on the web graph. Acacia (i) supports arbitrary feature dimensionalities and semantics without ad
arXiv:2609.31586v1 Announce Type: new Abstract: Decision Transformer performance degrades on long rollouts because the conditioning context drifts out of the training distribution. We show that this d
arXiv:2609.31463v1 Announce Type: cross Abstract: Infant movement analysis provides valuable biomarkers for the early identification of neurodevelopmental disorders. Recent advances in deep learning h
arXiv:2609.31491v1 Announce Type: new Abstract: Forecasting short-horizon mid-price movements from limit order book (LOB) data is central to algorithmic trading, yet most deep LOB forecasters are poin
arXiv:2609.31452v1 Announce Type: cross Abstract: Cloth manipulation is a challenging task due to the deformable and high-dimensional nature of cloth, which leads to complex interaction dynamics and p
arXiv:2609.31564v1 Announce Type: new Abstract: We show that neural network weights can be explicilty fintuned to admit a smaller grammar. Weight Pair Encoding (WeightPE) does so by placing a lossy Re
arXiv:2509.22796v2 Announce Type: replace-cross Abstract: Open-source software projects are foundational to modern software ecosystems, with the Linux kernel standing out as a critical exemplar due to
arXiv:2609.30721v1 Announce Type: new Abstract: Sliding-window classifiers are often evaluated on thousands of overlapping test windows, even though neighboring predictions share observations and rema
arXiv:2609.30286v1 Announce Type: cross Abstract: Short-term forecasting of cloud-induced power ramps across a network of distributed photovoltaic (PV) or irradiance sensors is a recognised pain point
arXiv:2609.31181v1 Announce Type: new Abstract: Black-box model identification works by scoring a model's response to natural-language prompts. One line of work feeds models a degenerate input -- thei
arXiv:2609.30963v1 Announce Type: new Abstract: Audio-driven streaming avatar generation requires real-time synthesis of speech-synchronized videos with dynamic and diverse motion. Self Forcing uses D
arXiv:2609.31193v1 Announce Type: new Abstract: Current Audio-Visual LLMs (AVLLMs) struggle with reasoning over videos featuring multi-speaker dialogues. In such videos, resolving 'who says what' is c
arXiv:2609.31293v1 Announce Type: cross Abstract: Speech-based screening is a promising, non-invasive approach for detecting Alzheimer's disease and related cognitive risks. However, models trained on
arXiv:2609.30805v1 Announce Type: cross Abstract: Industrial control system (ICS) threats documented for one plant can express cyber-physical effects relevant to another, but semantic similarity alone
I've been suspicious of the philosophers hired by Anthropic who specialize in AI ethics for similar reasons that I'm skeptical of those who went into 'bioethics': they form a closed subculture that de
Help: Project l'm building a shelf audit tool. A photo goes through YOLO, which crops each product, and then I embed the crop and search a small gallery of reference photos to get the SKU. New product