Knowledge catalogue
arXiv:2603.14659v2 Announce Type: replace-cross Abstract: Video reasoning requires models to locate and track question-relevant evidence across frames. While reinforcement learning (RL) with verifiabl
arXiv:2608.21878v1 Announce Type: new Abstract: Embodied Referring Expression Grounding is the task of enabling an agent to navigate in real environments and to localize a remote object based on natur
arXiv:2608.22521v1 Announce Type: new Abstract: Visual autoregressive (VAR) models have emerged as a fast, high-quality alternative to diffusion for text-to-image generation, but like diffusion models
arXiv:2608.21445v1 Announce Type: new Abstract: Automated seizure detection from electroencephalography (EEG) is essential for continuous neurological monitoring, particularly for subclinical epilepti
arXiv:2602.13880v2 Announce Type: replace Abstract: Graph property detection aims to determine whether a graph exhibits certain structural properties, such as being Hamiltonian. Recently, learning-bas
arXiv:2608.22081v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) enables large language models to incorporate external knowledge during generation, improving factual grounding an
arXiv:2608.21369v1 Announce Type: cross Abstract: Nigerian Pidgin is one of Africa's most widely spoken languages, yet remains severely underrepresented in language model evaluation. Existing benchmar
arXiv:2009.09083v4 Announce Type: replace-cross Abstract: The term intelligent system has emerged in the field of information technology as a category of computer systems derived from successful appli
arXiv:2608.22174v1 Announce Type: new Abstract: Unified multimodal models (UMMs) can perform both understanding and generation, raising a central question: can visual generation improve understanding?
arXiv:2608.23507v1 Announce Type: cross Abstract: Historical people may appear under different languages, scripts, and transcription traditions, while distinct individuals may share highly similar or
arXiv:2608.22127v1 Announce Type: new Abstract: Text-Attributed Graphs (TAGs) integrate graph structures and node-associated textual attributes, and recent studies have increasingly leveraged Large La
arXiv:2608.21439v1 Announce Type: new Abstract: Game world models have recently demonstrated promising capabilities in generating visually coherent and action-controllable gameplay videos. However, no
arXiv:2603.14254v2 Announce Type: replace Abstract: Test-time adaptation (TTA) aims to improve model robustness under distribution shifts by adapting to unlabeled test data, but most existing methods
arXiv:2608.20890v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have emerged as a powerful paradigm for end-to-end autonomous driving by jointly integrating perception, reasoning,
arXiv:2608.21186v1 Announce Type: new Abstract: Surgical procedures such as laparoscopic appendectomy are complex, high-stakes processes, yet formalizing their workflows for decision support remains a
arXiv:2608.20720v1 Announce Type: new Abstract: Open-world 3D affordance grounding requires localizing functional object parts in 3D given free-form language queries. Existing methods typically assume
arXiv:2608.20634v1 Announce Type: cross Abstract: Agents learn to act through interaction with environments, yet the environments used for training are often manually constructed or synthesized around
arXiv:2601.04786v3 Announce Type: replace-cross Abstract: Recent advances in large language models (LLMs) enable agentic systems trained with reinforcement learning (RL) over multi-turn interaction, b
arXiv:2608.21159v1 Announce Type: cross Abstract: Tool-using AI agents turn delegated tasks into provider effects, yet authorization often ends at admission while provider state, delivery, retry, and
arXiv:2508.14313v4 Announce Type: replace-cross Abstract: Test-time scaling strategies for Large Language Models predominantly rely on either reinforcement learning with sparse outcome rewards or sear
arXiv:2608.20666v1 Announce Type: cross Abstract: While Digital sky surveys provide excellent throughput of image data and can cover a large footprint, their imaging power is normally inferior to that
arXiv:2608.20434v1 Announce Type: cross Abstract: The coordination of multi-scale tasks is an effective strategy for computational materials discovery, yet the repeated application of diverse algorith
arXiv:2608.21187v1 Announce Type: cross Abstract: Pairwise reciprocal matrices are fundamental to the Analytic Hierarchy Process (AHP), a decision-making model. While the Direct Least Squares (DLS) me
// Applying Anthropic Primitives at Large Enterprises // Frontier models collapsed the cost of writing custom code. But they did not reduce the cost of reviewing and maintaining it. Each bespoke solut
arXiv:2608.20622v1 Announce Type: new Abstract: Frontier models have collapsed the cost of writing custom code: a niche problem a specialist sees in their own domain now costs an afternoon. The cost o
arXiv:2608.20637v1 Announce Type: cross Abstract: Static analyzers have been widely adopted for vulnerability detection in C/C++ programs. Query-based static analyzers (e.g., CodeQL) encode vulnerable
arXiv:2608.20699v1 Announce Type: new Abstract: Animating articulated 3D meshes via text requires satisfying strict kinematic constraints, modeling causal interactions between parts, and achieving ins
arXiv:2608.20369v1 Announce Type: cross Abstract: Structured reporting converts free-text radiology narratives into queryable data keys, facilitating cohort assembly, longitudinal tracking, and traini
arXiv:2608.21075v1 Announce Type: cross Abstract: This technical report presents AudioWorldSim, an open-source platform designed to generate realistic binaural audio datasets and advance research in a
arXiv:2608.20797v1 Announce Type: new Abstract: Evaluating language-guided mobile agents has recently shifted from rule-based to model-based approaches to achieve scalable and automated assessments. H
arXiv:2608.21249v1 Announce Type: new Abstract: While recent large language models (LLMs) have achieved promising results on individual patent drafting tasks, they fundamentally fail to investigate th
arXiv:2506.10903v2 Announce Type: replace Abstract: Statement autoformalization plays a crucial role in formal mathematical reasoning by enabling the automatic translation of natural language statemen
arXiv:2608.20349v1 Announce Type: cross Abstract: Large Language Models (LLMs) exhibit extreme sensitivity to surface-level prompt variations, in which minor lexical changes can trigger disproportiona
arXiv:2608.20691v1 Announce Type: new Abstract: Panoramic image generation is increasingly important for immersive applications such as virtual reality, augmented reality, and 3D content creation. Unl
arXiv:2608.20667v1 Announce Type: cross Abstract: Pseudo-label-based semi-supervised learning has achieved strong performance due to its simplicity and scalability. However, it is typically developed
arXiv:2506.13583v2 Announce Type: replace-cross Abstract: Reinforcement Learning (RL) agents often exhibit learning behaviors that are not intuitively interpretable by human observers, which can resul
arXiv:2608.21079v1 Announce Type: new Abstract: Adverse Pregnancy Outcomes (APOs) such as preterm birth and gestational diabetes can have long-term consequences for both the mother and child, yet an u
arXiv:2608.21060v1 Announce Type: new Abstract: Pathology foundation models (PFMs) are increasingly used as general-purpose backbones, yet existing benchmarks cannot systematically diagnose their whol
arXiv:2608.21101v1 Announce Type: cross Abstract: As large language model (LLM) agents move from conversation to executing code, reading local files, and orchestrating external tools, a single agent h
arXiv:2608.21278v1 Announce Type: new Abstract: Improving the safety of large language models (LLMs) often comes at the expense of utility, as globally applied safety tuning may affect model responses
arXiv:2608.21055v1 Announce Type: cross Abstract: Collaborative perception extends the sensing range of a single vehicle by fusing observations from nearby agents, which improves the robustness of aut
arXiv:2608.21142v1 Announce Type: new Abstract: Structured pruning reduces the size and inference cost of large language models (LLMs) by removing weight columns, but the resulting output error can de
arXiv:2608.21030v1 Announce Type: cross Abstract: Video multimodal large language models have advanced significantly, yet fine-grained motion-temporal understanding remains fragile. The core bottlenec
arXiv:2608.20562v1 Announce Type: cross Abstract: Mixed-type data containing both numerical and categorical variables arise in many scientific and real-world applications. Existing representation lear
arXiv:2608.20564v1 Announce Type: new Abstract: Multi-agent LLM systems can improve reasoning by pooling diverse perspectives, but their effectiveness depends on coordinating communication, particular
arXiv:2608.20561v1 Announce Type: cross Abstract: Diffusion models (DMs) have emerged as powerful generative priors for MRI reconstruction with promising results. Yet DM-based methods require extensiv
arXiv:2608.21041v1 Announce Type: cross Abstract: Geospatial representation learning from satellite imagery is a fundamental problem for large-scale urban analysis and real-world applications. Despite
arXiv:2504.11055v3 Announce Type: replace Abstract: Zero-shot anomaly detection and localization aims to learn from source-domain data and generalize to unseen target domains without target-domain sam
arXiv:2608.21207v1 Announce Type: cross Abstract: Imputing physiological time series (arterial blood pressure, blood glucose, etc.) is essential for addressing the missingness that pervades clinical d
arXiv:2608.21176v1 Announce Type: cross Abstract: Automatic speech quality assessment aims to predict Mean Opinion Scores (MOS) consistent with human subjective perception and is essential for evaluat
arXiv:2608.20440v1 Announce Type: cross Abstract: Authentication of edible oils in processed foods is important for food quality, fraud prevention, and regulatory compliance. This study establishes an
arXiv:2601.21948v2 Announce Type: replace Abstract: Neural visual decoding is a central problem in brain-computer interface research, aiming to reconstruct human visual perception and to elucidate the
arXiv:2608.20804v1 Announce Type: cross Abstract: Temporal Knowledge Graph (TKG) extrapolation seeks to infer future facts from time-varying relational histories. Recent diffusion-based approaches imp
arXiv:2601.12614v4 Announce Type: replace-cross Abstract: Hybrid-Vlasov simulations resolve ion-kinetic effects in the solar wind-magnetosphere interaction, but even 5D (2D + 3V) configurations are co
arXiv:2608.20515v1 Announce Type: new Abstract: Generative video compression can recover rich visual details at low bitrates, but simultaneously achieving high temporal consistency and low inference c
arXiv:2608.20759v1 Announce Type: new Abstract: Single-image 3D human reconstruction often suffers from over-smoothed textures and geometric inconsistencies. While diffusion models improve generative
arXiv:2608.20769v1 Announce Type: cross Abstract: Streaming emotion understanding uses historical state while continuously interpreting current audio, often feeding the model's previous prediction bac
arXiv:2608.21027v1 Announce Type: new Abstract: LLM agents are emerging as an important paradigm for real-world tasks that require reasoning, tool use, and sequential decision-making. As these agents
arXiv:2602.06159v3 Announce Type: replace Abstract: Driven by the emergence of Controllable Video Diffusion, existing Sim2Real methods for autonomous driving video generation typically rely on explici
arXiv:2608.20381v1 Announce Type: cross Abstract: Automating slide editing requires simultaneously satisfying modification accuracy, preservation fidelity, and robustness to deck length. Existing LLM-