Knowledge catalogue
arXiv:2608.24936v1 Announce Type: cross Abstract: We present GreenLeaf Law Embed Tiny, a 0.6B parameter embedding model for legal domain retrieval. GreenLeaf-Tiny achieves 75.11% on the Massive Legal
arXiv:2608.25261v1 Announce Type: cross Abstract: Mixture-of-experts (MoE) models combine specialized predictors under learned routing, offering a principled mechanism for leveraging heterogeneity in
Official Announcement: A First Look at Horus Cyber Nano 1.0 We are officially unveiling the first look at Horus Cyber Nano 1.0. This announcement presents the benchmark results of Horus Cyber Nano 1.0
arXiv:2608.26083v1 Announce Type: cross Abstract: Deep neural networks often exploit spurious associations in their training data, a failure known as shortcut learning. Concept-based explainability me
arXiv:2409.18073v2 Announce Type: replace-cross Abstract: For AI agents to be helpful to humans, they should be able to follow natural language instructions to complete everyday cooperative tasks in h
arXiv:2608.25291v1 Announce Type: new Abstract: Symbolic regression (SR) seeks to discover parsimonious mathematical laws from observational data, yet conventional approaches often struggle with the v
arXiv:2608.25548v1 Announce Type: new Abstract: Recently, there has been a growing adoption of protein language models (PLMs) in biomedical science. Their embeddings provide a rich numerical represent
arXiv:2608.25593v1 Announce Type: new Abstract: Agent capability is not determined by the model alone. The agent harness, encompassing memory management, planning strategy, action protocol, and tool/s
arXiv:2602.00686v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models have demonstrated remarkable generalization capabilities in robotic manipulation tasks, yet their substantial co
arXiv:2608.25115v1 Announce Type: new Abstract: Existing methods for improving Retrieval-Augmented Generation (RAG) efficiency mainly optimize downstream LLM generation, such as context compression or
arXiv:2608.25881v1 Announce Type: new Abstract: Fine-tuning abstractive summarization models requires high-quality annotated data. However, obtaining such corpora is expensive and time-consuming, as i
arXiv:2608.25874v1 Announce Type: new Abstract: This work tackles the problem of scalable perception for robotic packing with low-cost, low-resolution depth sensing. We propose a framework where recon
arXiv:2608.25176v1 Announce Type: new Abstract: Structural health monitoring (SHM) is essential in modern engineering, providing data for condition-based maintenance, lifecycle assessment, and predict
arXiv:2608.25864v1 Announce Type: new Abstract: Multi-arm collaboration is becoming a core capability in embodied manipulation. Recent vision-language-action (VLA) models integrate perception, languag
arXiv:2608.24946v1 Announce Type: new Abstract: Macros constitute a large part of the core area in modern very large-scale integration (VLSI) designs. Moreover, macro positions have a significant impa
arXiv:2608.25738v1 Announce Type: cross Abstract: Spiking Neural Networks (SNNs) are increasingly distributed as pretrained checkpoints and reused as backbones for new tasks. However, current SNN wate
arXiv:2608.25733v1 Announce Type: new Abstract: The existing methods for saliency detection task focus on the application of multi-level features, aiming to take advantage of the respective strengths
arXiv:2606.17118v2 Announce Type: replace Abstract: Mixture-of-Experts Multimodal Large Language Models (MoE-MLLMs) offer remarkable performance but incur prohibitive GPU memory costs, making compress
arXiv:2608.25768v1 Announce Type: new Abstract: Turkish encoder models have adopted modern architectures while leaving the pretraining objective fixed at masked language modelling. This paper introduc
Most companies manage their org chart, their product line, their brand guidelines, their operations manual. Each as a separate document. Each updated on its own cadence. Each a snapshot of a different
arXiv:2608.24937v1 Announce Type: new Abstract: Multi-Modal Anomaly Detection (MMAD) detects rare abnormal events from heterogeneous data sources and is increasingly used in safety- and reliability-cr
arXiv:2503.13048v4 Announce Type: replace Abstract: Electrical Impedance Tomography (EIT) offers a promising solution for distributed tactile sensing with minimal wiring and full-surface coverage in r
arXiv:2608.25126v1 Announce Type: new Abstract: Machine learning has had a significant positive impact on the prediction of athlete performance and injury risk. Most works in this field rely on subjec
arXiv:2608.25327v1 Announce Type: new Abstract: Physics-Informed Neural Networks (PINNs) frequently fail on stiff or advection-dominated PDEs, and two recent accounts offer competing remedies: switchi
arXiv:2608.25080v1 Announce Type: new Abstract: Time series forecasting models are widely used in high-stakes settings, yet their predictions remain difficult to interpret because existing post-hoc me
arXiv:2608.25038v1 Announce Type: new Abstract: We introduce grounded glossary generation, a structured task requiring models to recover semantically meaningful Sanskrit phrases and produce translatio
arXiv:2608.25970v1 Announce Type: new Abstract: Multimodal medical prediction often faces incomplete pairing: auxiliary modalities with complementary signal are available for only a subset of subjects
arXiv:2608.24905v1 Announce Type: cross Abstract: Service robots may encounter ambiguous user requests that require context-aware inference. Users may also have unique preferences with certain tasks w
arXiv:2608.25486v1 Announce Type: cross Abstract: Long Narrative Reasoning is an essential capability for processing and reasoning over complex narratives. While retrieval-augmented generation provide
arXiv:2608.25495v1 Announce Type: new Abstract: Human-robot interaction (HRI) requires robots to interpret human actions early in their execution in order to respond safely, efficiently, and naturally
arXiv:2608.25858v1 Announce Type: new Abstract: High-resolution precipitation fields are essential for hydrological impact assessment, yet global climate model outputs are too coarse and biased for di
Putting this tweet in the “scary” category of AI. Calling upon the non-technical business professionals that follow me to pay attention. I’m breaking down the key parts of the @RyanGreenblatt tweet on
Pythian deployed Gemini Enterprise to employees. Pythian reported 80% shorter database incident resolution time using AI in a Google Cloud guest post.
arXiv:2608.25585v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models provide a versatile foundation for general robotic manipulation, yet they exhibit significant brittleness when confr
arXiv:2608.25366v1 Announce Type: new Abstract: In this paper, we propose RAEM, a robust autonomous exploration framework for quadruped robots operating in multi-floor environments. Most existing grou
arXiv:2509.08897v2 Announce Type: replace-cross Abstract: With the rapid advancement of multimodal retrieval and its application in LLMs and multimodal LLMs, increasingly complex retrieval tasks have
arXiv:2510.09062v2 Announce Type: replace Abstract: Recent advances in long chain-of-thought (CoT) reasoning have largely prioritized answer accuracy and token efficiency, while overlooking aspects cr
arXiv:2608.26101v1 Announce Type: new Abstract: Recent advances in video editing have been largely driven by large-scale instruction-based datasets. However, existing datasets still suffer from two cr
arXiv:2608.25487v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has emerged as a powerful architecture for Question Answering (QA) by integrating external information into Large L
arXiv:2608.25467v1 Announce Type: new Abstract: Multimodal regression suffers from the mean-collapse pathology: under squared loss, an unconstrained regressor converges to the conditional mean, which
arXiv:2608.25133v1 Announce Type: new Abstract: The development of federated learning (FL) techniques has helped improve the privacy preservation of users' data and extended the applications of machin
arXiv:2608.24977v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) enhances large language models by grounding outputs in external knowledge, improving factuality and reducing hall
arXiv:2608.25017v1 Announce Type: new Abstract: A latent world model trains its decoder on latents anchored to observations, then deploys it on the model's own free-running rollout, hundreds of steps
arXiv:2608.25102v1 Announce Type: new Abstract: The Robot Operating System 2 (ROS2) has become a widely adopted framework for the development of distributed robotic systems. However, its communication
arXiv:2608.25367v1 Announce Type: new Abstract: Underwater unimodal object detection faces many challenges in sensor imaging, such as optical images limited by underwater noise and visible distance, a
arXiv:2506.23492v2 Announce Type: replace-cross Abstract: Recent advances in deep learning have significantly improved predictive accuracy. However, modern neural networks remain systematically overco
arXiv:2608.25304v1 Announce Type: cross Abstract: Multinomial choice models allow flexible substitution patterns but become computationally demanding with many alternatives or observations. With a fix
arXiv:2505.23022v2 Announce Type: replace Abstract: Large Language Model (LLM) serving increasingly underpins online Web services such as conversational agents, Web search, and programming assistants,
arXiv:2603.16558v2 Announce Type: replace Abstract: Large Vision-Language Models (LVLMs) achieve strong performance on many multimodal tasks, but object hallucinations severely undermine their reliabi
arXiv:2608.25282v1 Announce Type: new Abstract: Mixed-Integer Linear Programming (MILP) is a fundamental optimization paradigm in combinatorial optimization and has been widely applied across real-wor
arXiv:2608.25246v1 Announce Type: new Abstract: Badminton is a compact but challenging domain for game AI: a player must choose a physically feasible shuttle trajectory, anticipate the opponent's inte
arXiv:2608.25193v1 Announce Type: cross Abstract: Smart freight corridors offer a practical pathway for connected and automated vehicle (CAV) deployment in freight transportation, but physical experim
arXiv:2608.25990v1 Announce Type: new Abstract: Orthogonal optimisers such as Muon can substantially accelerate large language model pretraining relative to Adam, yet the mechanism remains incompletel
arXiv:2601.06472v2 Announce Type: replace Abstract: Learning solution operators for differential equations with neural networks has shown great potential in scientific computing, but ensuring their st
arXiv:2608.26081v1 Announce Type: cross Abstract: Collective intelligence can emerge when individuals coordinate through a shared environment, allowing local actions to accumulate into durable social
arXiv:2608.25756v1 Announce Type: new Abstract: Reinforcement learning post-training drives reasoning and agentic capabilities in modern AI systems, yet a growing body of work shows that it is most ef
arXiv:2608.25935v1 Announce Type: new Abstract: Traffic Anomaly Understanding (TAU) requires models and systems to detect, reason about, and explain anomalous events in transportation videos. To addre
arXiv:2608.25088v1 Announce Type: new Abstract: Cortical computation is strikingly low-dimensional: a handful of latent variables, carried in a neural population's activity, steer the higher-dimension
arXiv:2511.15343v2 Announce Type: replace Abstract: Autonomous navigation in complex scenes requires reliable perception across scenarios that the model did not encounter during its training. Along it
arXiv:2608.25897v1 Announce Type: new Abstract: Explaining deep learning models operating on time series data is crucial in various applications that require transparent and interpretable insights int