Knowledge catalogue
arXiv:2605.14443v1 Announce Type: new Abstract: The shift toward interacting with frozen, 'black-box' Large Language Models (LLMs) has transformed prompt engineering from a heuristic exercise into a c
arXiv:2605.15110v1 Announce Type: cross Abstract: Adaptations of features commonly applied in the field of visual computing, co-occurrence matrix (COM) and run-length matrix (RLM), are proposed for th
arXiv:2605.14113v1 Announce Type: cross Abstract: While interpretable prototype networks offer compelling case-based reasoning for clinical diagnostics, their raw continuous outputs lack the semantic
arXiv:2605.14534v1 Announce Type: cross Abstract: Evaluating object removal in images and videos remains challenging because the task is inherently one-to-many, yet existing metrics frequently disagre
arXiv:2602.07441v2 Announce Type: replace-cross Abstract: Offline reinforcement learning (RL), which optimizes policies using a previously collected static dataset, is an important branch of RL. A pop
arXiv:2602.04289v2 Announce Type: replace Abstract: Modern language models are trained almost exclusively on token sequences produced by a fixed tokenizer, an external lossless compressor often over U
arXiv:2605.14045v1 Announce Type: new Abstract: Adverse weather removal (AWR) in real-world images remains challenging due to heterogeneous and unseen degradations, while distortion-driven training of
arXiv:2605.14559v1 Announce Type: new Abstract: PyCSP^3 provides a productive way to build constraint models for solving combinatorial constrained problems and export them to XCSP^3, preserving a comp
arXiv:2605.14188v1 Announce Type: cross Abstract: What does a book look like to a quantum computer? This paper takes eight classical works of the Renaissance and its late-antique inheritance -- from A
arXiv:2605.15000v1 Announce Type: cross Abstract: Premature closure, or committing to a conclusion before sufficient information is available, is a recognized contributor to diagnostic error but remai
arXiv:2605.14502v1 Announce Type: cross Abstract: Power electronics systems are increasingly exposed to cyber threats due to their integration with digital controllers and communication networks. Howe
arXiv:2605.15185v1 Announce Type: cross Abstract: Generative video models are increasingly studied as implicit world models, yet evaluating whether they produce physically plausible 3D structure and m
arXiv:2605.14235v1 Announce Type: new Abstract: We present an empirical evaluation of quantum entanglement in agent coordination within quantum multi agent reinforcement learning (QMARL). While QMARL
arXiv:2511.17367v2 Announce Type: replace Abstract: Computing worst-case robust strategies in pursuit-evasion games (PEGs) is time-consuming, especially when real-world factors like partial observabil
arXiv:2605.14026v1 Announce Type: cross Abstract: For reinforcement learning in data-scarce domains like real-world robotics, intensive data reuse enhances efficiency but induces overfitting. While pr
Retrieval-Augmented Generation (RAG) is a technique that enhances large language models (LLMs) by enabling them to access and utilize external knowledge sources during response generation. This likely
arXiv:2507.05193v4 Announce Type: replace-cross Abstract: Rheumatoid arthritis (RA) is a common autoimmune disease that has been the focus of research in computer-aided diagnosis (CAD) and disease mon
arXiv:2605.14351v1 Announce Type: cross Abstract: We present a physics-informed framework for system identification based on randomized stable atomic features. Impulse responses are represented as ran
arXiv:2510.20206v2 Announce Type: replace Abstract: Prompt design plays a crucial role in text-to-video (T2V) generation, yet user-provided prompts are often short, unstructured, and misaligned with t
This appears to be a social media post by Elon Musk on X (formerly Twitter) responding to or commenting on a user (@raqisright) with a dismissive characterization of Instagram as primarily for women.
arXiv:2605.15190v1 Announce Type: new Abstract: Causal autoregressive video diffusion models support real-time streaming generation by extrapolating future chunks from previously generated content. Di
arXiv:2605.14232v1 Announce Type: new Abstract: This paper addresses the motion control problem for mobile robots in obstacle-cluttered environments. The mobile robot has partial environment informati
Nous Research announced a collaboration or release involving Grok and Hermes models through xAI's official blog. The post likely details the integration, performance characteristics, or technical deta
arXiv:2605.13900v1 Announce Type: cross Abstract: In large-scale multi-agent systems with shared resource constraints, an upstream planner must iteratively evaluate candidate resource plans -- assessi
arXiv:2605.14939v1 Announce Type: cross Abstract: Reliable position and shape control in tokamak plasmas requires accurate real-time regulation of several strongly coupled shape parameters. The contro
arXiv:2605.14462v1 Announce Type: new Abstract: Recovering 4D human-object interaction (HOI) from monocular video is a key step toward scalable 3D content creation, embodied AI, and simulation-based l
arXiv:2605.13852v1 Announce Type: cross Abstract: We often aim to generate images that are both photorealistic and 3D-consistent, adhering to precise geometry, material, and viewpoint controls. Typica
Clem Delangue expresses optimism about the role of American open source AI development within the broader AI ecosystem, highlighting the significant experimentation and creative innovation occurring i
arXiv:2605.14867v1 Announce Type: cross Abstract: Spike activity has been the dominant neural signal for behavior decoding due to its high spatial and temporal resolution. However, as brain-computer i
arXiv:2507.21433v3 Announce Type: replace-cross Abstract: Large Reasoning Models (LRMs) are becoming integral to many AI inference systems, enhancing their capabilities with advanced reasoning. Howeve
arXiv:2601.03630v2 Announce Type: replace Abstract: This paper presents the first systematic comparison investigating whether Large Reasoning Models (LRMs) are superior judges to non-reasoning LLMs. O
Telco cloud modernization has become an urgent operational imperative for operators burdened by decades of siloed infrastructure and the demands of 5G, 6G and edge AI. A unified platform approach is n
arXiv:2605.14486v1 Announce Type: new Abstract: As the misuse of AI-generated images grows, generalizable image detection techniques are urgently needed. Recent state-of-the-art (SOTA) methods adopt a
arXiv:2605.15196v1 Announce Type: new Abstract: Video generation powers a vast array of downstream applications. However, while the de facto standard, i.e., latent diffusion models, typically employ h
arXiv:2605.14019v1 Announce Type: cross Abstract: Regret is the cost of uncertainty in algorithmic decision-making. Quantifying regret typically requires computationally expensive simulation via Sampl
arXiv:2603.12554v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) has been effective for post-training autoregressive (AR) language models, but extending these methods to diffusion
arXiv:2605.14126v1 Announce Type: cross Abstract: Fast Healthcare Interoperability Resources (FHIR) is the dominant standard for interoperable exchange of healthcare data. In FHIR, electronic health r
arXiv:2605.14366v1 Announce Type: new Abstract: Extending large language models (LLMs) to low-resource languages often incurs an 'alignment tax': improvements in the target language come at the cost o
arXiv:2605.14063v1 Announce Type: new Abstract: Continual test-time adaptation (CTTA) updates a pretrained model online on an unlabeled, non-stationary stream while anchoring it to a frozen source che
arXiv:2605.14563v1 Announce Type: cross Abstract: Automated code documentation is essential for modern software development, providing the contextual grounding that both human developers and coding ag
arXiv:2605.14686v1 Announce Type: new Abstract: Tabular data sharing under privacy constraints is increasingly important for research and collaboration. Synthetic data generators (SDGs) are a promisin
arXiv:2512.12083v3 Announce Type: replace Abstract: Semantic-rich features from Vision Foundation Models (VFMs) have been leveraged to enhance Latent Diffusion Models (LDMs). However, raw VFM features
Zac Hall / 9to5Mac: Replit says it has “worked things out with Apple”, which has approved a Replit update after four months, following a reported dispute over vibe coding apps — All's well that ends w
arXiv:2605.14913v1 Announce Type: new Abstract: Linear attention has emerged as a promising direction for scaling Vision Transformers beyond the quadratic cost of dense self-attention. A prevalent str
arXiv:2603.16039v2 Announce Type: replace-cross Abstract: Recent work has made clear that the residual pathway is not mere optimization plumbing; it is part of the model's representational machinery.
arXiv:2605.14558v1 Announce Type: cross Abstract: Agentic reinforcement learning trains large language models using multi-turn trajectories that interleave long reasoning traces with short environment
Ollama announced a command-line feature allowing users to restore the Codex application to its previous state without applying any effects or modifications. The command `ollama launch codex-app --rest
In this post, we walk through how to configure document-level ACLs for your S3 knowledge base in Amazon Quick. You will learn how to set up and verify an ACL configuration that enforces document-level
arXiv:2605.14075v1 Announce Type: cross Abstract: Large language models (LLMs) have revolutionized natural language processing. Understanding their internal mechanisms is crucial for developing more i
arXiv:2605.13932v1 Announce Type: new Abstract: Robust prediction of molecular properties under extreme out-of-distribution (OOD) scenarios is a pivotal bottleneck in AI-driven drug discovery. Current
arXiv:2512.21651v2 Announce Type: replace Abstract: Large Language Models (LLMs) deliver strong performance across a wide range of NLP tasks, but their massive sizes hinder deployment on resource-cons
arXiv:2605.14145v1 Announce Type: new Abstract: The field of deep visual recognition is undergoing a paradigm shift toward universal representations. The Platonic Representation Hypothesis suggests th
arXiv:2511.13026v3 Announce Type: replace Abstract: Self-reflection mechanisms that rely on purely text-based rethinking processes perform well in most multimodal tasks. However, when directly applied
arXiv:2605.14497v1 Announce Type: cross Abstract: Offline-to-online reinforcement learning harnesses the stability of offline pretraining and the flexibility of online fine-tuning. A key challenge lie
arXiv:2605.14925v1 Announce Type: new Abstract: Drone-view geo-localization aims to match a query drone image, often captured under adverse weather conditions (e.g., rain, snow, fog), against a galler
arXiv:2603.02115v2 Announce Type: replace-cross Abstract: General-purpose robot reward models are typically trained to predict absolute task progress from expert demonstrations, providing only local,
arXiv:2602.05285v2 Announce Type: replace Abstract: A core challenge in structural biophysics is generating biomolecular conformations that are both physically plausible and consistent with experiment
Cowboy Space has filed FCC plans for a 20,000-satellite 'Stampede' orbital data center constellation, after raising $275 million to develop rockets whose upper stages would serve as computing platform
arXiv:2605.14152v1 Announce Type: cross Abstract: Safety evaluations for large language models (LLMs) increasingly target high-stakes National Security and Public Safety (NSPS) risks, yet multilingual
arXiv:2605.15154v1 Announce Type: cross Abstract: Feature attribution analysis is critical for interpreting machine learning models and supporting reliable data-driven decisions. However, feature attr