Knowledge catalogue
arXiv:2511.21777v2 Announce Type: replace Abstract: Methane is a potent greenhouse gas, responsible for roughly 30% of warming since pre-industrial times. A small number of large point sources account
arXiv:2604.21233v1 Announce Type: cross Abstract: Toward the goal of using Scientific Machine Learning (SciML) emulators to improve the numerical representation of aerosol processes in global atmosphe
arXiv:2604.20850v1 Announce Type: cross Abstract: Dense retrieval systems rank passages by embedding similarity to a query, but multi-hop questions require passages that are associatively related thro
arXiv:2601.11194v2 Announce Type: replace Abstract: We suggest a new multi-modal algorithm for joint inference of paired structurally aligned samples with Rectified Flow models. While some existing me
arXiv:2603.01170v2 Announce Type: replace-cross Abstract: This work presents ATLAS, an LLM-driven framework that bridges standardized threat modeling and property-based formal verification for System-
arXiv:2510.05482v2 Announce Type: replace Abstract: Molecular dynamics (MD) simulations underpin modern computational drug discovery, materials science, and biochemistry. Recent machine learning model
arXiv:2604.20844v1 Announce Type: cross Abstract: Recent GraphRAG methods integrate graph structures into text indexing and retrieval, using knowledge graph triples to connect text chunks, thereby imp
arXiv:2604.21289v1 Announce Type: new Abstract: Facial attribute editing aims to modify target attributes while preserving attribute-irrelevant content and overall image fidelity. Existing GAN-based m
arXiv:2604.21530v1 Announce Type: cross Abstract: Lung adenocarcinoma (LUAD) grading depends on accurately identifying growth patterns, which are indicators of prognosis and can influence treatment de
arXiv:2604.20936v1 Announce Type: cross Abstract: We present AttentionBender, a tool that manipulates cross-attention in Video Diffusion Transformers to help artists probe the internal mechanics of bl
arXiv:2604.21766v1 Announce Type: new Abstract: Existing audio question answering benchmarks largely emphasize sound event classification or caption-grounded queries, often enabling models to succeed
arXiv:2512.06171v2 Announce Type: replace Abstract: Shearography is an interferometric technique sensitive to surface displacement gradients, providing high sensitivity for detecting subsurface defect
arXiv:2602.08561v3 Announce Type: replace-cross Abstract: Reproducing computational research is often assumed to be as simple as rerunning the original code with provided data. In practice, missing pa
arXiv:2604.21772v1 Announce Type: new Abstract: Test-Time Adaptation (TTA) aims to mitigate distributional shifts between training and test domains during inference time. However, existing TTA methods
arXiv:2511.07752v3 Announce Type: replace Abstract: Contextual predictability shapes how we choose and encode words in production. The effects of a word's predictability given preceding or past contex
arXiv:2601.06428v3 Announce Type: replace Abstract: Diffusion Language Models (DLMs) decode multiple tokens in parallel, but aggressive multi-token decoding amplifies cross-token dependency errors and
arXiv:2305.01626v4 Announce Type: replace-cross Abstract: Computational models of syntax are predominantly text-based. Here we propose that the most basic first step in the evolution of syntax can be
arXiv:2604.21083v1 Announce Type: cross Abstract: Third-party Large Language Model (LLM) API gateways are rapidly emerging as unified access points to models offered by multiple vendors. However, the
arXiv:2601.10863v3 Announce Type: replace Abstract: Traditional time series forecasting methods optimize for accuracy alone. This objective neglects temporal consistency, in other words, how consisten
arXiv:2604.21849v1 Announce Type: cross Abstract: Bayesian Optimal Experimental Design (BOED) provides a rigorous framework for decision-making tasks in which data acquisition is often the critical bo
arXiv:2604.21724v1 Announce Type: new Abstract: Large token-indexed lookup tables provide a compute-decoupled scaling path, but their practical gains are often limited by poor parameter efficiency and
arXiv:2604.21134v1 Announce Type: new Abstract: Vision-Language Models (VLMs) frequently misread values, hallucinate details, and confuse overlapping elements in charts. Current approaches rely solely
arXiv:2604.21344v1 Announce Type: cross Abstract: Charts are widely used to present complex information. Deriving meaningful insights in real-world contexts often requires interpreting multiple relate
arXiv:2504.07940v3 Announce Type: replace Abstract: 360{eg} videos have emerged as a promising medium to represent our dynamic visual world. Compared to the 'tunnel vision' of standard cameras, their
arXiv:2604.20906v1 Announce Type: cross Abstract: The rapid growth of scientific software has created practical barriers for bioinformatics research. Although powerful statistical, artificial intellig
arXiv:2604.21508v1 Announce Type: new Abstract: Protein-ligand bioactivity data published in the literature are essential for drug discovery, yet manual curation struggles to keep pace with rapidly gr
arXiv:2604.04395v2 Announce Type: replace Abstract: 3D conducting motion generation aims to synthesize fine-grained conductor motions from music, with broad potential in music education, virtual perfo
arXiv:2604.21854v1 Announce Type: new Abstract: Artificial intelligence now decides who receives a loan, who is flagged for criminal investigation, and whether an autonomous vehicle brakes in time. Go
arXiv:2604.20945v1 Announce Type: cross Abstract: Effective safety auditing of large language models (LLMs) demands tools that go beyond black-box probing and systematically uncover vulnerabilities ro
arXiv:2604.20994v1 Announce Type: cross Abstract: The growth of agentic AI has drawn significant attention to function calling Large Language Models (LLMs), which are designed to extend the capabiliti
arXiv:2601.17747v2 Announce Type: replace Abstract: Change detection (CD) aims to identify surface changes from multi-temporal remote sensing imagery. In real-world scenarios, Pixel-level change label
arXiv:2604.21743v1 Announce Type: new Abstract: Image enhancement models for mobile devices often struggle to balance high output quality with the fast processing speeds required by mobile hardware. W
arXiv:2604.21430v1 Announce Type: new Abstract: Moral judgements form the foundation of human social behavior and societal systems. While Artificial Intelligence chatbots increasingly serve as persona
arXiv:2604.21718v1 Announce Type: cross Abstract: Video-language models (VLMs) learn to reason about the dynamic visual world through natural language. We introduce a suite of open datasets, benchmark
arXiv:2504.11159v2 Announce Type: replace Abstract: In high-stakes domains, such as healthcare and industry, the explainability of AI-based decision-making has become crucial. Without insight into mod
arXiv:2604.21260v1 Announce Type: cross Abstract: We study semisupervised mean estimation with a small labeled sample, a large unlabeled sample, and a black-box prediction model whose output may be mi
arXiv:2604.21277v1 Announce Type: new Abstract: We introduce MMTR-Bench, a benchmark designed to evaluate the intrinsic ability of Multimodal Large Language Models (MLLMs) to reconstruct masked text d
arXiv:2604.21251v1 Announce Type: cross Abstract: Large language models (LLMs) trained on unfiltered corpora inherently risk retaining sensitive information, necessitating selective knowledge unlearni
arXiv:2510.15313v2 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly applied to creative domains, yet their performance in classical Chinese poetry generation and evaluati
arXiv:2604.21352v1 Announce Type: new Abstract: Mental health challenges are increasing worldwide, straining emotional support services and leading to counselor overload. This can result in delayed re
arXiv:2604.20845v1 Announce Type: cross Abstract: Next Point-of-Interest (POI) recommendation plays a crucial role in location-based services by predicting users' future mobility patterns. Existing me
arXiv:2604.21654v1 Announce Type: cross Abstract: Existing deep network-based full-reference image quality assessment (FR-IQA) models typically work by performing pairwise comparisons of deep features
arXiv:2509.20712v5 Announce Type: replace-cross Abstract: Reinforcement learning (RL) has become a powerful paradigm for optimizing large language models (LLMs) to handle complex reasoning tasks. A co
arXiv:2507.03806v3 Announce Type: replace-cross Abstract: This paper presents a learning-based framework for approximating an exact magnetic-field interaction model, supported by both numerical and ex
arXiv:2604.21369v1 Announce Type: new Abstract: Human activity recognition (HAR) in Internet of Things (IoT) environments must cope with heterogeneous sensor settings that vary across datasets, device
arXiv:2509.24239v4 Announce Type: replace-cross Abstract: Recent large language models (LLMs) have shown strong reasoning capabilities. However, a critical question remains: do these models possess ge
arXiv:2604.21573v1 Announce Type: new Abstract: Spatial transcriptomics (ST) enables spatially resolved gene profiling but remains expensive and low-throughput, limiting large-cohort studies and routi
arXiv:2604.21308v1 Announce Type: cross Abstract: Enterprise LLM agents can dramatically improve workplace productivity, but their core capability, retrieving and using internal context to act on a us
arXiv:2604.21085v1 Announce Type: cross Abstract: Accurate representation of moist convective sub-grid-scale processes remains a major challenge in global climate models, as traditional parameterizati
arXiv:2604.20967v1 Announce Type: new Abstract: Upper-limb exoskeletons (ULEs) have the potential to restore functional independence in individuals with severe motor impairments; however, the clinical
arXiv:2604.20869v1 Announce Type: cross Abstract: Background: More than 80% of U.S. cancer care is delivered in community settings, where survival remains worse than at academic centers. Clinicians mu
arXiv:2604.21060v1 Announce Type: new Abstract: Accurate diagnosis of pediatric brain tumors, starting with histopathology, presents unique challenges for deep learning, including severe data scarcity
arXiv:2604.20924v1 Announce Type: new Abstract: Timely and interpretable early warning of sepsis remains a major clinical challenge due to the complex temporal dynamics of physiological deterioration.
arXiv:2604.21270v1 Announce Type: cross Abstract: There has been remarkable progress over the past decade in establishing finite-sample, non-asymptotic bounds on recovering unknown system parameters f
arXiv:2604.20987v1 Announce Type: new Abstract: Long horizon interactive environments are a testbed for evaluating agents skill usage abilities. These environments demand multi step reasoning, the cha
arXiv:2604.21584v1 Announce Type: new Abstract: Feature discovery from complex unstructured data is fundamentally a reasoning problem: it requires identifying abstractions that are predictive of a tar
arXiv:2603.18677v2 Announce Type: replace-cross Abstract: Artificial intelligence is increasingly embedded in human decision making. In some cases, it enhances human reasoning. In others, it fosters e
arXiv:2604.21789v1 Announce Type: cross Abstract: Competing firms that serve shared customer populations face a fundamental information aggregation problem: each firm holds fragmented signals about ri
arXiv:2604.21546v1 Announce Type: new Abstract: Out-of-Distribution (OOD) detection requires sensitivity to subtle shifts without overreacting to natural In-Distribution (ID) diversity. However, from
arXiv:2509.23744v3 Announce Type: replace-cross Abstract: Multimodal large language models (MLLMs) promise enhanced reasoning by integrating diverse inputs such as text, vision, and audio. Yet cross-m