Knowledge catalogue
arXiv:2604.12184v1 Announce Type: new Abstract: TRUST Agents is a collaborative multi-agent framework for explainable fact verification and fake news detection. Rather than treating verification as a
arXiv:2604.12015v1 Announce Type: cross Abstract: In-context learning (ICL) performance depends critically on which demonstrations are placed in the prompt, yet most existing selectors prioritize heur
arXiv:2604.12346v1 Announce Type: new Abstract: Spatio-temporal video grounding (STVG) aims to localize queried objects within dynamic video segments. Prevailing fully-trained approaches are notorious
arXiv:2604.11913v1 Announce Type: new Abstract: Nutrition estimation of meals from visual data is an important problem for dietary monitoring and computational health, but existing approaches largely
arXiv:2509.17995v2 Announce Type: replace-cross Abstract: Recent advances have shown that scaling test-time computation enables large language models (LLMs) to solve increasingly complex problems acro
arXiv:2604.12798v1 Announce Type: cross Abstract: FlashAttention-style online softmax enables exact attention computation with linear memory by streaming score tiles through on-chip memory and maintai
arXiv:2602.22394v2 Announce Type: replace Abstract: Vision Transformers (ViTs), when pre-trained on large-scale data, provide general-purpose representations for diverse downstream tasks. However, art
arXiv:2604.12044v1 Announce Type: cross Abstract: Deep learning models may converge to suboptimal solutions despite strong validation accuracy, masking an optimization failure we term Trajectory Devia
arXiv:2604.12831v1 Announce Type: new Abstract: Indoor fire disasters pose severe challenges to autonomous search and rescue due to dense smoke, high temperatures, and dynamically evolving indoor envi
This Reddit thread from r/MachineLearning reflects community skepticism about the peer review standards at top ML conferences, with a user expressing surprise that a particular paper received an oral
arXiv:2603.05295v3 Announce Type: replace Abstract: We introduce WebChain, the largest open-source dataset of human-annotated trajectories on real-world websites, designed to accelerate reproducible r
arXiv:2603.05044v2 Announce Type: replace Abstract: Current paradigms for training GUI agents are fundamentally limited by a reliance on either unsafe, non-reproducible live web interactions or costly
arXiv:2604.12540v1 Announce Type: cross Abstract: Data scarcity limits NLP development for low-resource African languages. We evaluate two data augmentation methods -- LLM-based generation (Gemini 2.5
arXiv:2604.12358v1 Announce Type: new Abstract: Recently, visual token pruning has been studied to handle the vast number of visual tokens in Multimodal Large Language Models. However, we observe that
arXiv:2507.09318v2 Announce Type: replace-cross Abstract: Generating spoken dialogue is inherently more complex than monologue text-to-speech (TTS), as it demands both realistic turn-taking and the ma
arXiv:2604.09996v1 Announce Type: new Abstract: Accurate apple detection in orchard images is important for yield prediction, fruit counting, robotic harvesting, and crop monitoring. However, changing
arXiv:2604.09932v1 Announce Type: cross Abstract: Hybrid approaches that combine data-driven learning with physics-based insight have shown promise for improving the reliability of industrial conditio
arXiv:2604.10177v1 Announce Type: cross Abstract: We study the piecewise-stationary restless multi-armed bandit (PS-RMAB) problem, where each arm evolves as a Markov chain but mean rewards may change
arXiv:2604.10058v1 Announce Type: new Abstract: In this paper, we discuss an efficient algorithm for computing the growth distance between two compact convex sets with representable support functions.
arXiv:2510.10182v2 Announce Type: replace-cross Abstract: Reasoning is an important task for large language models (LLMs). Among all the reasoning paradigms, inductive reasoning is one of the fundamen
arXiv:2508.09977v4 Announce Type: replace Abstract: In the context of novel view synthesis, 3D Gaussian Splatting (3DGS) has recently emerged as an efficient and competitive counterpart to Neural Radi
arXiv:2604.11048v1 Announce Type: cross Abstract: Imbuing Large Language Models (LLMs) with specific personas is prevalent for tailoring interaction styles, yet the impact on underlying cognitive capa
arXiv:2512.05534v4 Announce Type: replace-cross Abstract: As AI models achieve remarkable capabilities across diverse domains, understanding what representations they learn and how they encode concept
arXiv:2511.06609v3 Announce Type: replace Abstract: The accurate forecasting of complex, high-dimensional dynamical systems from observational data is a fundamental task across numerous scientific and
arXiv:2604.10157v1 Announce Type: cross Abstract: Band gap engineering of oxide semiconductors through doping is critical for photocatalysis and optoelectronics, yet the combinatorial space of dopant
arXiv:2511.18082v3 Announce Type: replace Abstract: Recent Vision-Language-Action (VLA) models have shown impressive flexibility and generalization, yet their deployment in robotic manipulation remain
arXiv:2604.09630v1 Announce Type: cross Abstract: This study investigates the adoption and effectiveness of AI-based anomaly detection in cross-provider electronic health record (EHR) environments. It
arXiv:2510.01544v2 Announce Type: replace Abstract: Diffusion-based large language models offer a non-autoregressive alternative for text generation, but enabling them to perform complex reasoning rem
arXiv:2601.09211v2 Announce Type: replace Abstract: This paper addresses the problem of affordance grounding from RGBD images of an object, which aims to localize surface regions corresponding to a te
arXiv:2604.10513v1 Announce Type: new Abstract: AI agent development relies heavily on natural language prompting to define agents' tasks, knowledge, and goals. These prompts are interpreted by Large
arXiv:2604.11753v1 Announce Type: new Abstract: We study parallel test-time scaling for long-horizon agentic tasks such as agentic search and deep research, where multiple rollouts are generated in pa
arXiv:2604.09576v1 Announce Type: new Abstract: Deploying continual object detection on microcontrollers (MCUs) with under 100KB memory requires efficient feature compression that can adapt to evolvin
arXiv:2604.11135v1 Announce Type: cross Abstract: Pretrained video generation models provide strong priors for robot control, but existing unified world action models still struggle to decode reliable
arXiv:2603.18492v2 Announce Type: replace Abstract: Mixture-of-Experts (MoE) language models increase parameter capacity without proportional per-token compute, but the deployment still requires stori
arXiv:2602.07153v2 Announce Type: replace Abstract: End-to-end GUI agents for real desktop environments require large amounts of high-quality interaction data, yet collecting human demonstrations is e
arXiv:2604.10702v1 Announce Type: cross Abstract: Multi-parametric prostate MRI -- combining T2-weighted, apparent diffusion coefficient, and high b-value diffusion-weighted sequences -- is central to
arXiv:2604.09690v1 Announce Type: new Abstract: Jaguar re-identification (re-ID) from citizen-science imagery can look strong on standard retrieval metrics while still relying on the wrong evidence, s
arXiv:2604.09619v1 Announce Type: cross Abstract: The integration of Large Language Models (LLMs) into educational ecosystems promises to democratize access to personalized tutoring, yet the readiness
arXiv:2604.10708v1 Announce Type: cross Abstract: Recent progress in multimodal models has spurred rapid advances in audio understanding, generation, and editing. However, these capabilities are typic
Reuters: AWS launches Amazon Bio Discovery, an AI-powered application designed to speed up drug development, giving scientists access to biological foundation models — Amazon's (AMZN.O) cloud unit on
arXiv:2604.11628v1 Announce Type: new Abstract: Existing conversational memory systems rely on complex hierarchical summarization or reinforcement learning to manage long-term dialogue history, yet re
arXiv:2604.09748v1 Announce Type: cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) is an emerging paradigm that significantly boosts a Large Language Model's (LLM's) reasoning abi
arXiv:2604.11560v1 Announce Type: cross Abstract: 1. Natural sounds have been recorded for millions of hours over the previous decades using passive acoustic monitoring. Improvements in deep learning
arXiv:2510.20792v4 Announce Type: replace-cross Abstract: The rapid progress of graph generation has raised new security concerns, particularly regarding backdoor vulnerabilities. While prior work has
arXiv:2604.09671v1 Announce Type: new Abstract: We propose a stronger formulation of RL on top of RWKV-style recurrent sequence models, in which the fixed-size recurrent state is explicitly interprete
arXiv:2604.10865v1 Announce Type: new Abstract: Deep Clustering (DC) has emerged as a powerful tool for tabular data analysis in real-world domains like finance and healthcare. However, most existing
arXiv:2603.08942v2 Announce Type: replace-cross Abstract: Recent advances in vision-language models (VLMs) have demonstrated remarkable zero-shot capabilities, yet adapting these models to specialized
arXiv:2603.13941v2 Announce Type: replace Abstract: Growing waste streams and the transition to a circular economy require efficient automated waste sorting. In industrial settings, materials move on
arXiv:2604.10541v1 Announce Type: new Abstract: Facial action unit (AU) detection and facial expression (FE) recognition can be jointly viewed as affective facial behavior tasks, representing fine-gra
arXiv:2503.02983v2 Announce Type: replace-cross Abstract: Traditional methods for system discovery frequently struggle with efficient data usage and uncertainty quantification. Identifying the governi
arXiv:2604.10389v1 Announce Type: new Abstract: Terminology substitution errors in clinical notes, where one medical term is replaced by a linguistically valid but clinically different term, pose a pe
arXiv:2604.11162v1 Announce Type: new Abstract: Accurate defect segmentation is critical for industrial inspection, yet dense pixel-level annotations are rarely available. A common workaround is to co
arXiv:2604.11136v1 Announce Type: cross Abstract: Object-level spatial-temporal understanding is essential for video question answering, yet existing multimodal large language models (MLLMs) encode fr
arXiv:2604.11234v1 Announce Type: new Abstract: Text-guided multispectral object detection uses text semantics to guide semantic-aware cross-modal interaction between RGB and IR for more robust percep
arXiv:2604.11424v1 Announce Type: new Abstract: Speech Language Models (SLMs) exhibit strong semantic understanding, yet their generated speech often sounds flat and fails to convey expressive intent,
arXiv:2604.11483v1 Announce Type: new Abstract: Goal-directed molecular generation requires satisfying heterogeneous constraints such as protein--ligand compatibility and multi-objective drug-like pro
arXiv:2604.10696v1 Announce Type: new Abstract: We present Camyla, a system for fully autonomous research within the scientific domain of medical image segmentation. Camyla transforms raw datasets int
arXiv:2601.06993v2 Announce Type: replace Abstract: Multi-modal large language models (MLLMs) exhibit strong general-purpose capabilities, yet still struggle on Fine-Grained Visual Classification (FGV
arXiv:2604.10420v1 Announce Type: new Abstract: Large language models (LLMs) enable waveform-to-text ECG interpretation and interactive clinical questioning, yet most ECG-LLM systems still rely on wea
arXiv:2604.10504v1 Announce Type: new Abstract: Current large language models (LLMs), even those explicitly trained for reasoning, often struggle with ambiguous content moderation cases due to mislead