Knowledge catalogue
arXiv:2503.10118v3 Announce Type: replace-cross Abstract: The sim-to-real gap remains a critical challenge in robotics, hindering the deployment of algorithms trained in simulation to real-world syste
arXiv:2609.39584v1 Announce Type: cross Abstract: Edge computing has emerged as a critical computing paradigm in modern distributed systems by migrating data processing closer to end users and Interne
arXiv:2609.39071v1 Announce Type: new Abstract: Legal language models require reward signals that capture not only answer correctness but also the multidimensional quality of legal responses. Existing
arXiv:2609.39911v1 Announce Type: new Abstract: Patient preference, defined as a patient's demonstrated willingness and capacity to adhere to clinical recommendations, is a primary determinant of ther
arXiv:2404.11624v2 Announce Type: replace-cross Abstract: We introduce the Token Space, a categorical framework for AI computations. A Token is a finite tuple whose entries are elements of a carrier s
arXiv:2602.14049v2 Announce Type: replace-cross Abstract: Spatio-temporal traffic forecasting is a core component of intelligent transportation systems, supporting various downstream tasks such as sig
arXiv:2607.11386v2 Announce Type: replace Abstract: UAV swarm for applications, such as indoor inspection, security patrol, and logistics delivery, are often mission-oriented rather than exploration-o
arXiv:2609.37454v1 Announce Type: new Abstract: Underwriters in commercial Property and Casualty (P&C) insurance spend 30 to 40% of their time on administrative work rather than risk judgment, and a s
arXiv:2609.35958v1 Announce Type: cross Abstract: We introduce Solver Agent, an AI framework based on large language models for calculations and proofs in mathematics and theoretical physics. The solu
arXiv:2609.35437v1 Announce Type: cross Abstract: Quantitative characterization of lymph node morphology is important for assessing axillary lymph node metastasis in breast cancer. However, surfaces r
arXiv:2510.17611v3 Announce Type: replace Abstract: Unsupervised anomaly detection (UAD) has evolved from specialized single-class models to unified multi-class models, yet existing multi-class models
arXiv:2609.31731v1 Announce Type: new Abstract: In this paper, we propose GERIS, a game-theoretic framework for instance selection in the data augmentation phase of license plate recognition systems.
OpenAI: OpenAI is adopting a structured “safety case” documentation framework modeled after industries like aviation and nuclear power to govern frontier RL training — Loading... We believe we are ent
arXiv:2609.31197v1 Announce Type: new Abstract: Machine learning for scientific discovery is almost systematically data bound. Producing relevant high quality data, under budget constraints, is amongs
Apropos NVidia’s agent trust framework, anybody remember NemoClaw? Anyone using it? Introducing the NemoClaw Deep Agents Blueprint, a reference architecture for building open agent systems developed w
arXiv:2609.30508v1 Announce Type: new Abstract: The aim of this work is to examine the connectomes of Caenorhabditis elegans through a computational lens using the reservoir computing framework. Conne
arXiv:2609.30747v1 Announce Type: cross Abstract: As artificial intelligence (AI) becomes embedded in everyday life, its environmental footprint, particularly water consumption remains largely invisib
arXiv:2605.05725v2 Announce Type: replace Abstract: Time-series anomaly detection often returns scores or intervals, while analysts need to understand the abnormal behavior and the evidence supporting
arXiv:2609.29724v1 Announce Type: new Abstract: On-demand delivery platforms pay riders through incentive activities whose tiers are set from recent completions of riders with a similar history. Opera
arXiv:2609.28476v1 Announce Type: cross Abstract: While a number of methods exist for counting pedestrians in street-view imagery, these mostly ignore the social dimensions of pedestrian activity. A s
arXiv:2603.04756v3 Announce Type: replace Abstract: MOOSEnger is a modeling and simulation AI agent framework for the Multiphysics Object-Oriented Simulation Environment (MOOSE) ecosystem, built aroun
💯💯”The current agentic framework is fully unsafe and must be redesigned from scratch based on different fundamental principles.” Some observations around the interview Q:Can be AI test environments be
arXiv:2609.27621v1 Announce Type: new Abstract: Physical modeling and inverse design require computation that can continue from reusable state. We introduce SHRAV, an architecture-independent computat
arXiv:2609.23421v1 Announce Type: cross Abstract: Standard data center sustainability metrics, including Power Usage Effectiveness (PUE), Water Usage Effectiveness (WUE), and Carbon Usage Effectivenes
arXiv:2609.22664v1 Announce Type: cross Abstract: Research on large language model agents for penetration testing is evaluated almost entirely by capability: whether the agent captures a flag or repro
arXiv:2407.09693v3 Announce Type: replace Abstract: The field of Neural-Symbolic (NeSy) systems is growing rapidly. Proposed approaches show great promise in achieving symbiotic unions of neural and s
arXiv:2609.24761v1 Announce Type: new Abstract: Aerial manipulators represent the forefront of aerial robotics. Although potentially capable of complex interaction tasks, controlling aerial manipulato
arXiv:2609.22252v1 Announce Type: new Abstract: We present CALM, a reproducible hybrid framework that integrates an optional large language model (LLM) activity planner with calibrated stochastic choi
arXiv:2512.23348v3 Announce Type: replace-cross Abstract: We introduce a data-analysis framework based on filtrations of finite topological spaces. Starting from a finite metric data set, we construct
arXiv:2609.22647v1 Announce Type: new Abstract: Visual representations can help lower-primary learners understand Math Word Problems, but generating classroom-usable visuals remains difficult. Existin
arXiv:2410.23912v3 Announce Type: replace-cross Abstract: The reasoning abilities of large language models (LLMs) have improved with chain-of-thought (CoT) prompting, allowing models to solve complex
Introducing Halo, the best framework for post-training of open-source models. Halo delivers up to 2.8x the throughput of stock TRL with less peak memory, while models stay in their native HuggingFace
arXiv:2405.20174v3 Announce Type: replace Abstract: We propose a computational tropical geometry framework for the symbolic analysis of neural networks with tropical activations. The number of linear
arXiv:2609.20641v1 Announce Type: cross Abstract: Physics-informed neural networks and finite element methods provide two different paradigms for the numerical approximation of partial differential eq
arXiv:2609.18281v1 Announce Type: new Abstract: The availability and consistency of online services remain vulnerable due to Distributed Denial of Service (DDoS) attacks. These attacks are evolving by
arXiv:2601.00743v2 Announce Type: replace Abstract: Integrating symbolic constraints into deep learning models could make them more robust, interpretable, and data-efficient. Still, it remains a time-
arXiv:2609.18521v1 Announce Type: cross Abstract: Speech retrieval has become increasingly important as spoken content continues to grow across meetings, lectures, podcasts, and videos. Existing bench
arXiv:2609.17556v1 Announce Type: cross Abstract: Edge-deployed AI operate under dynamically changing power budgets, reliability requirements, and input distributions, requiring continuous adaptation.
arXiv:2609.17171v1 Announce Type: cross Abstract: The interpretability of complex machine learning models is of paramount importance, especially in real-world high-stakes domains such as healthcare an
arXiv:2609.16485v1 Announce Type: cross Abstract: We develop a certified continuation framework for equilibrium computation and for training deep equilibrium networks (DEQs), with training formulated
arXiv:2609.16852v1 Announce Type: new Abstract: Industrial IoT environments increasingly deploy autonomous mobile robots for tasks such as material handling, product assembly, or infrastructure inspec
arXiv:2609.16589v1 Announce Type: new Abstract: As Large Language Models (LLMs) increasingly handle complex subjective tasks, aligning their intentions and behaviors with human values has become a cri
arXiv:2609.17247v1 Announce Type: new Abstract: An agentic AI driver-assistance framework that integrates perception, compliance reasoning, vehicle-state interpretation, and safety arbitration into a
Our framework for reporting model misalignment https://openai.com/index/model-misalignment-reporting-framework/ // if you scrape away all the anthropomorphic language, all the nonsense about thinking,
arXiv:2609.17349v1 Announce Type: cross Abstract: In embodied cyber-physical systems, active cyberattacks pose an immediate threat not just to data, but to physical integrity and human safety. While e
arXiv:2609.17019v1 Announce Type: new Abstract: While Chain-of-Thought (CoT) reasoning has been proven to be effective, it often leads to overthinking, resulting in computational overhead, inference l
arXiv:2609.14419v1 Announce Type: cross Abstract: Person re-identification (ReID) is essential for multi-camera surveillance and tracking, yet remains difficult due to viewpoint and illumination chang
arXiv:2609.14178v1 Announce Type: new Abstract: The rapid diffusion of hate speech and misinformation on social networks challenges democratic societies, since direct suppression efforts may deepen po
arXiv:2609.13624v1 Announce Type: cross Abstract: Large Language Models (LLMs) are powerful zero-shot learners but remain prone to misalignment with human preferences, often producing biased, toxic, o
arXiv:2609.13191v1 Announce Type: new Abstract: The rapid expansion of operational satellites and orbital debris has increased the frequency of close approach events in low Earth orbit (LEO), creating
arXiv:2512.09944v4 Announce Type: replace Abstract: Echocardiography interpretation requires integrating multi-view temporal evidence with quantitative measurements and guideline-grounded reasoning, y
Elon just gave a much more practical explanation of the current AI safety problem....and laid out a practical framework for making frontier AI safer OpenAI and Anthropic are the two leading AI compani
arXiv:2609.15772v1 Announce Type: cross Abstract: Spiking neural networks (SNNs) have shown promise for sparse, event-driven computation through stateful processing that is naturally compatible with l
arXiv:2609.13406v1 Announce Type: new Abstract: When we speak of recursive self-improvement (RSI), are we speaking of a phenomenon, a mechanism, or a prospect? Towards autonomous and evolving intellig
arXiv:2601.00900v2 Announce Type: replace-cross Abstract: As a critical application of computational intelligence in remote sensing, deep learning-based synthetic aperture radar (SAR) image target rec
arXiv:2609.13514v1 Announce Type: new Abstract: Ensuring the reliability of black-box machine learning models in safety-critical space missions remains a significant challenge, particularly when groun
arXiv:2609.14015v1 Announce Type: new Abstract: Schizophrenia is a serious psychiatric disorder that affects millions of people worldwide, and its diagnosis remains primarily dependent on clinical ass
arXiv:2609.13856v1 Announce Type: new Abstract: Enterprise customer support systems must answer customer questions correctly, retrieve the right policy information, use customer context, and pass diff
arXiv:2609.12544v1 Announce Type: new Abstract: Clinical de-identification relies on accurately identifying personally identifiable information (PII). However, manually annotated datasets are costly t
arXiv:2609.12724v1 Announce Type: cross Abstract: sEMG is vulnerable to various contaminants that distort signal morphology and spectral content. Accurate signal quality assessment (SQA) is essential