Knowledge catalogue
arXiv:2605.03820v1 Announce Type: new Abstract: Multimodal learning often grapples with the challenge of low-quality data, which predominantly manifests as two facets: modality imbalance and noisy cor
arXiv:2605.01120v1 Announce Type: new Abstract: The Zarankiewicz number extbf{Z}(m, n, s, t) is the maximum number of edges in a bipartite graph G_{m, n} such that there is no complete K_{s, t} bipart
arXiv:2605.02255v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in interactive and retrieval-augmented settings, raising significant privacy concerns. While at
arXiv:2605.03283v1 Announce Type: cross Abstract: We provide a unified theoretical analysis of Linear Discriminant Analysis with simultaneous multilabel scatter matrix formulations and Stiefel orthogo
arXiv:2605.03098v1 Announce Type: new Abstract: Deep learning-based medical image segmentation is increasingly used to support clinical diagnosis and develop new treatment strategies. However, model p
arXiv:2605.04036v1 Announce Type: cross Abstract: Deep search capabilities have become an indispensable competency for frontier Large Language Model (LLM) agents, yet their development remains dominat
arXiv:2605.02938v1 Announce Type: new Abstract: Reliable periodic patterns serve as a fundamental basis for accurate multivariate time series forecasting. However, existing methods either implicitly e
arXiv:2605.03615v1 Announce Type: new Abstract: Engagement estimation from face video remains challenging because facial evidence is often incomplete, labeled data are limited, and engagement annotati
arXiv:2605.04018v1 Announce Type: new Abstract: Reasoning-intensive retrieval aims to surface evidence that supports downstream reasoning rather than merely matching topical similarity. This capabilit
arXiv:2603.15969v2 Announce Type: replace Abstract: The Romansh language has several regional varieties, called idioms, which sometimes have limited mutual intelligibility. Despite this linguistic div
arXiv:2605.03706v1 Announce Type: new Abstract: Zero-shot Named Entity Recognition (ZS-NER) remains brittle under domain and schema shifts, where unseen label definitions often misalign with a large l
Singular Bank leverages OpenAI's ChatGPT and Codex to accelerate banking operations and developer productivity. The integration enables bankers and software engineers to streamline workflows, automate
arXiv:2604.04328v3 Announce Type: replace-cross Abstract: The evaluation of general-purpose artificial agents, particularly those based on LLMs, presents a significant challenge due to the non-transit
arXiv:2605.03874v1 Announce Type: new Abstract: Classification of EEG signals using shallow Convolutional Neural Networks (CNNs) is a prevalent and successful approach across a variety of fields. Most
arXiv:2605.03221v1 Announce Type: new Abstract: Long-tailed class distributions are pervasive in multi-class medical datasets and pose significant challenges for deep learning models which typically u
arXiv:2605.00914v1 Announce Type: cross Abstract: Multi-agent debate, where teams of LLMs iteratively exchange rationales and vote on answers, is widely deployed under the assumption that peer review
arXiv:2605.03642v1 Announce Type: new Abstract: Open-vocabulary object detection aims to recognize objects from an open set of categories, which leverages vision-language models (VLMs) pre-trained on
arXiv:2408.01055v2 Announce Type: replace-cross Abstract: Self-healing systems have long been a focus of research, aiming to enable software to recover from unexpected runtime errors without human int
arXiv:2605.01102v1 Announce Type: new Abstract: Single-agent systems (SAS) have become the default pattern for LLM-driven scientific workflows, but routing planning, tool use, and synthesis through a
I recently talked with Joseph Ruscio about AI coding tools for Heavybit's High Leverage podcast: Ep. #9, The AI Coding Paradigm Shift with Simon Willison. Here are some of my highlights, including my
Anthropic announced a major compute partnership with SpaceX involving over 300 MW of new computational capacity and 220,000 NVIDIA GPUs to be brought online within one month, dedicated to powering Cla
arXiv:2605.02463v1 Announce Type: cross Abstract: Multi-agent LLM systems are increasingly used to solve complex tasks through decomposition, debate, specialization, and ensemble reasoning. However, t
arXiv:2605.03596v1 Announce Type: cross Abstract: Workspace learning requires AI agents to identify, reason over, exploit, and update explicit and implicit dependencies among heterogeneous files in a
arXiv:2605.00858v1 Announce Type: cross Abstract: Owing to the recent advancements in wearable devices for health care, the importance of BP estimation without cuffs increases. Cuff technologies are i
arXiv:2605.02507v1 Announce Type: new Abstract: Accurate prediction of Remaining Useful Life (RUL) in aero-engines is vital for predictive maintenance, improved operational reliability, and reduced li
arXiv:2605.01657v1 Announce Type: new Abstract: Vision-Language Models (VLMs) typically rely on static initial frames for video reasoning, restricting their ability to incorporate essential dynamic in
arXiv:2605.01968v1 Announce Type: new Abstract: Offline reinforcement learning (RL) can fail spectacularly when bootstrapped temporal-difference (TD) updates amplify their own errors, driving the crit
arXiv:2602.05353v3 Announce Type: replace-cross Abstract: Large Language Models have shown strong capabilities in complex problem solving, yet many agentic systems remain difficult to interpret and co
arXiv:2605.00937v1 Announce Type: cross Abstract: We propose an arbitrary Lagrangian-Eulerian (ALE)-consistent machine learning framework for long-term fluid-structure interaction (FSI) prediction on
arXiv:2605.02259v1 Announce Type: new Abstract: Incomplete propagation data significantly hinders robust fake news detection. Recent approaches leverage large language models to simulate missing user
arXiv:2605.02667v1 Announce Type: cross Abstract: Dense and accurate depth estimation is essential for robotic manipulation, grasping, and navigation, yet currently available depth sensors are prone t
arXiv:2605.02651v1 Announce Type: cross Abstract: Scientific peer review increasingly struggles to assess reproducibility at the scale and complexity of modern research output. Evaluating reproducibil
arXiv:2605.01148v1 Announce Type: cross Abstract: Does structure in representations imply structure in computation? We study how Llama-3.1-8B reasons over cyclic concepts (e.g., 'what month is six mon
arXiv:2605.02630v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have enabled autonomous GUI agents that translate natural language instructions into executable screen coordinates. Howeve
arXiv:2605.01074v1 Announce Type: cross Abstract: Associative memory or content-addressable memory is an important component function in computer science and information processing, and at the same ti
arXiv:2605.01681v1 Announce Type: new Abstract: Virtual screening performance depends heavily on the chosen docking and scoring methods. Recent AI-based tools such as DiffDock and NMDN have reported s
arXiv:2605.02009v1 Announce Type: cross Abstract: Building on recent advances in representation learning for wireless channels, this work investigates the cost-benefit trade-offs of high-dimensional c
Meta is facing a class action lawsuit filed by five major book publishers and one author over claims the company 'engaged in one of the most massive infringements of copyrighted materials in history'
arXiv:2401.16764v5 Announce Type: replace Abstract: Witnessing the evolution of text-to-image diffusion models, significant strides have been made in text-to-3D generation. Currently, two primary para
arXiv:2605.01006v1 Announce Type: new Abstract: Partisan news media erode cross-partisan trust, but large language models (LLMs) offer a potential means of debiasing such content at scale. Across two
arXiv:2601.13398v2 Announce Type: replace Abstract: LLMs demonstrate strong performance on code benchmarks, yet consistent reasoning across forward and backward execution remains elusive. We present R
arXiv:2605.02357v1 Announce Type: new Abstract: In 3D point cloud understanding, the core challenge lies in accurately capturing discriminative features within complex neighborhoods, which directly af
arXiv:2605.01011v1 Announce Type: new Abstract: Medical large language model (LLM) evaluations rely on simplified, exam-style benchmarks that rarely reflect the ambiguity of real-world medical inquiri
arXiv:2509.04470v2 Announce Type: replace Abstract: Autonomous agents executing human instructions must operate reliably even when instructions are incomplete. While recent approaches improve detectio
arXiv:2605.01323v1 Announce Type: new Abstract: In this article, we introduce SiNFluD, a novel benchmark dataset for Sindhi figurative language classification. We first collect raw text from various b
arXiv:2602.15823v2 Announce Type: replace Abstract: A central challenge in large language model (LLM) editing is capability preservation: methods that successfully change targeted behavior can quietly
arXiv:2605.02089v1 Announce Type: new Abstract: Handwritten Text Recognition (HTR) under limited labeled data remains a challenging problem, particularly for Arabic-script languages. Although modern s
Release: datasette-llm 0.1a7 Mechanism for configuring default options for specific models. Part of Datasette's evolving support mechanism for plugins that use LLMs. It's now possible to configure a m
🚀 Day-0 MTP support for Gemma4 now available at vLLM with ready-to-use docker image! ⚡️Enjoy up to 3x faster decoding performance to supercharge your development with zero quality degradation! Check o
arXiv:2605.00977v1 Announce Type: cross Abstract: The record of the beginning of the most widespread legal system in the world is contained in millions of pages of handwritten text. Most of the record
arXiv:2605.00941v1 Announce Type: cross Abstract: Flow matching has become a leading framework for generative modeling, but quantifying the uncertainty of its samples remains an open problem. Existing
arXiv:2605.02196v1 Announce Type: new Abstract: Machine unlearning aims to remove specified training data to satisfy privacy regulations such as GDPR. However, existing evaluations assume identical pr
arXiv:2605.00327v1 Announce Type: cross Abstract: In large language model (LLM)-based recommendation systems, direct preference optimization (DPO) effectively aligns recommendations with user preferen
arXiv:2605.02275v1 Announce Type: new Abstract: Place recognition is essential for long-term autonomous navigation, enabling loop closure and consistent mapping. Although deep learning has improved pe
arXiv:2605.01315v1 Announce Type: new Abstract: This paper investigates sentiment classification of Steam game reviews using an attention-based Bidirectional Long Short-Term Memory (BiLSTM) model. Usi
arXiv:2605.01266v1 Announce Type: new Abstract: Zero-shot vision-language models (VLMs) offer a promptable alternative to task-specific training for gross tumor volume (GTV) delineation in non-small-c
arXiv:2605.01264v1 Announce Type: cross Abstract: Traditional approaches to test case generation often involve manual effort and incur significant computational overhead. Additionally, these approache
arXiv:2605.02815v1 Announce Type: new Abstract: Text-to-SQL over large analytical databases requires navigating complex schemas, resolving ambiguous queries, and grounding decisions in actual data. Mo
arXiv:2605.01561v1 Announce Type: cross Abstract: This paper develops a Hall-Sandpile model of economic instability that combines a Hall-like transversal stress mechanism with sandpile threshold dynam
arXiv:2605.02596v1 Announce Type: new Abstract: With each sensing modality exhibiting inherent strengths and limitations, multi-modal approaches for wearable Human Activity Recognition (HAR) are becom