Knowledge catalogue
arXiv:2409.12500v2 Announce Type: replace-cross Abstract: Large language models have become increasingly popular and demonstrated remarkable performance in various natural language processing (NLP) ta
arXiv:2610.21591v1 Announce Type: new Abstract: Machine learning (ML) for analog IC design is constrained by limited open data and the absence of standardized evaluation: results reported in different
arXiv:2610.21503v1 Announce Type: new Abstract: Reliable worker localization is essential for real-time industrial safety management, but seamless outdoor-indoor positioning remains challenging. GNSS
arXiv:2310.17882v3 Announce Type: replace Abstract: By aggregating distributed energy resources (DERs) into a single dispatchable resource, virtual power plants (VPPs) enable the grid to use the flexi
arXiv:2610.21852v1 Announce Type: new Abstract: Solving optimal control problems for high-dimensional mechanical systems subject to constraints remains challenging due to nonlinear dynamics and non-co
arXiv:2610.21685v1 Announce Type: cross Abstract: Adaptive assessment systems personalize learning by estimating learner proficiency and recommending suitable questions. However, many existing approac
arXiv:2610.20632v1 Announce Type: new Abstract: Modern healthcare generates increasingly complex medical reports that challenge clinical professionals in terms of time and interpretive burden. Manual
arXiv:2610.21292v1 Announce Type: new Abstract: Maintaining small path-tracking errors under moving reference frames is essential for robotic manipulation tasks with tight execution tolerances, such a
arXiv:2610.20797v1 Announce Type: new Abstract: Reliable absolute heading estimation is critical for road-vehicle navigation, particularly when magnetic, inertial, or GNSS-based references are degrade
arXiv:2610.21679v1 Announce Type: new Abstract: Tokenization is a critical component of the language modeling pipeline, but it is poorly understood. Tokenizers can impact downstream performance, but t
arXiv:2610.21342v1 Announce Type: new Abstract: The task of constructing a predictor that is simultaneously accurate under multiple evaluation metrics has been popularized recently under the name omni
arXiv:2610.20875v1 Announce Type: new Abstract: Sustainably powered mobile robots enable long-duration observational missions by harvesting energy from the environment. However, effective autonomy req
arXiv:2610.21743v1 Announce Type: new Abstract: Direct pairwise AUC-surrogate training is attractive because it trains toward the ranking metric used at test time, especially under class imbalance. Th
arXiv:2406.20031v2 Announce Type: replace-cross Abstract: Pairwise difference learning (PDL) has recently been introduced as a new meta-learning technique for regression. Instead of learning a mapping
arXiv:2610.20619v1 Announce Type: cross Abstract: Super-resolution machine learning methods hold promise for addressing the high computational costs associated with high-dimensional features in tradit
arXiv:2610.21390v1 Announce Type: cross Abstract: Multi-agent large language model (LLM) systems are increasingly deployed at the edge to support complex tasks that require collaboration and informati
arXiv:2610.22056v1 Announce Type: new Abstract: Traditional reinforcement learning (RL) algorithms face significant limitations in handling long-term tasks with sparse rewards. Recent advancements hav
arXiv:2610.20935v1 Announce Type: new Abstract: Engineering agents must produce artifacts that satisfy exact, coupled constraints. Existing solutions often require agents to make semantic decisions an
arXiv:2610.21640v1 Announce Type: new Abstract: Reinforcement learning (RL) has been a critical paradigm for improving large language model (LLM) reasoning and agentic capabilities, but its efficiency
arXiv:2610.21539v1 Announce Type: new Abstract: Diffusion models (DMs) have steadily demonstrated outstanding performance in high-fidelity, controllable generation across diverse scenarios, following
arXiv:2610.22051v1 Announce Type: cross Abstract: In the best-arm identification problem, an algorithm adaptively selects arms to find the arm of the largest mean reward. Successive Rejects (SR) is a
arXiv:2610.21042v1 Announce Type: cross Abstract: Systematic literature reviews follow the PRISMA process of screening scholarly works and extracting evidence from included studies. Deep research tool
arXiv:2505.15737v3 Announce Type: replace Abstract: Reconstructing high-fidelity underwater scenes remains a challenging task due to light absorption, scattering, and limited visibility inherent in aq
arXiv:2610.21061v1 Announce Type: cross Abstract: Discrete diffusion models have become a powerful framework for modeling complex discrete distributions across a range of applications. While theoretic
arXiv:2603.10599v2 Announce Type: replace-cross Abstract: We present a JAX implementation of the Self-Scaled Broyden family of quasi-Newton methods, fully compatible with JAX and building on the Optim
arXiv:2606.20022v2 Announce Type: replace-cross Abstract: Contextual bandit learning has attracted increasing attention in engineering applications due to its ability to incorporate side/context infor
arXiv:2610.22217v1 Announce Type: cross Abstract: Reinforcement learning (RL) can elicit specialized visual capabilities in vision-language models (VLMs), yet jointly optimizing heterogeneous objectiv
arXiv:2610.21089v1 Announce Type: new Abstract: Slip-induced falls when riding motorcycles are difficult to avoid even for expert riders and represent a major cause of single-vehicle accidents. Despit
arXiv:2610.20968v1 Announce Type: cross Abstract: Executing heavy-duty physical manipulation in unpredictable environments remains a major challenge for quadrupedal robots lacking dedicated manipulato
arXiv:2610.21742v1 Announce Type: new Abstract: Echo State Networks (ESNs), as lightweight implementations of reservoir computing, provide efficient solutions for temporal data processing in resource-
Surprised that so few people are talking about this. Persistence has become a core capability of recent models (Opus 5.5, GPT 6 Astra, Gemini 4 Argon,...). I was just reading through the Gemini 4 Argo
arXiv:2509.26226v3 Announce Type: replace-cross Abstract: Reinforcement Learning with Verifiable Reward (RLVR) effectively solves complex tasks but demands extremely long context lengths during traini
arXiv:2602.23959v2 Announce Type: replace Abstract: Recent MLLMs increasingly rely on visual chain-of-thought to perform region-grounded reasoning over images. However, existing approaches ground regi
arXiv:2610.21978v1 Announce Type: new Abstract: Biological visual navigation achieves remarkable robustness at extremely low power, whereas frame-based robotic systems relying on artificial neural net
arXiv:2504.05607v2 Announce Type: replace-cross Abstract: Despite the success of Large Language Models (LLMs) in long-context tasks, their reliability in recognizing unanswerable questions remains a c
arXiv:2610.21456v1 Announce Type: new Abstract: Recent multilingual large language models achieve strong translation performance, yet the internal mechanisms responsible for low-resource multilingual
TL;DR -- Interpretability might be way more tractable than we thought, and the guy who helped convince everyone otherwise is now saying we can understand models by directly studying neurons and their
arXiv:2610.22232v1 Announce Type: new Abstract: Lossless image compression fundamentally relies on accurate entropy modeling, driving a recent shift toward large language model (LLM)-based methods. Ho
arXiv:2610.21128v1 Announce Type: cross Abstract: Label-free evaluation methods, such as self-consistency filtering, majority-vote aggregation, and agreement-based reliability scoring, rely on an impl
arXiv:2610.20824v1 Announce Type: cross Abstract: Wolof is spoken by 23M people, mostly in Senegal, but remains weakly supported by open-weight language models, while API models raise cost, governance
arXiv:2610.18301v1 Announce Type: new Abstract: Recent progress in autoformalisation of mathematics using AI has been impressive. Measuring this progress requires datasets of formal statements that ar
arXiv:2503.14555v2 Announce Type: replace-cross Abstract: Traditional multi-agent reinforcement learning (MARL) systems can develop cooperative strategies through repeated interactions. However, these
arXiv:2610.19395v1 Announce Type: new Abstract: Robotic vascular intervention can reduce radiation exposure to physicians and improve manipulation stability, but effective guidance remains challenging
arXiv:2610.14818v1 Announce Type: new Abstract: Agentic AI moves generative AI applications toward systems that coordinate reasoning, enterprise context, model inference, and external actions. Integra
arXiv:2610.19413v1 Announce Type: new Abstract: Virtual reality training for robot-assisted vascular intervention requires accurate robotic control and effective feedback on guidewire--vessel interact
arXiv:2610.16049v1 Announce Type: cross Abstract: Existing audio deepfake detection (ADD) methods frequently exhibit limited generalization, as fixed bottleneck architectures fail to adapt to the hete
arXiv:2610.17710v1 Announce Type: new Abstract: Training graphical user interface (GUI) agents with reinforcement learning suffers from sparse outcome rewards, leading to inefficient learning. Process
arXiv:2610.18603v1 Announce Type: new Abstract: Benchmarks report what an Artificial Intelligence (AI) agent can do on a task suite, but not whether one released version has been engineered with the c
arXiv:2610.14823v1 Announce Type: cross Abstract: Artificial intelligence is increasingly used to support product management tasks. At the same time, AI-native research and development (R&D) may incre
arXiv:2610.14382v1 Announce Type: new Abstract: Agentic AI systems operating over geospatial data require more than autonomous reasoning and tool use; they must also support explicit orchestration, sp
arXiv:2610.18083v1 Announce Type: new Abstract: Scaling recursive self-improvement requires additional computation to produce useful research progress in reaching persistent objectives. Intuitively, m
arXiv:2610.20141v1 Announce Type: new Abstract: In various industries, smoke and fire are two of the most important threats in the workplace. One of the common methods for detecting smoke and fire is
arXiv:2610.20486v1 Announce Type: new Abstract: In reinforcement learning, an agent must explore an unknown environment to learn how to make good decisions. Unlike methods that can freely sample any s
arXiv:2610.18889v1 Announce Type: cross Abstract: Estimating (heterogeneous) treatment effects is still challenging when the outcome is semicontinuous (i.e., exhibiting both a discrete point mass at z
arXiv:2311.04902v3 Announce Type: replace Abstract: Large Language Models (LLMs) with billions of parameters are prime targets for network pruning, which removes some model weights without hurting per
arXiv:2610.20319v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) are increasingly deployed in safety-critical domains, yet their susceptibility to backdoor attacks remains a fo
arXiv:2610.19603v1 Announce Type: new Abstract: Transformers have demonstrated strong performance in long-term time series forecasting (LTSF), yet modeling non-stationary temporal dependencies remains
arXiv:2610.19882v1 Announce Type: new Abstract: Instruction-driven image editing has reached native 4K, yet how such editors are trained remains undisclosed, and pretraining one from scratch is beyond
arXiv:2610.16511v1 Announce Type: new Abstract: Pattern mining is a valuable tool for exploratory data analysis, but identifying relevant patterns for a specific user is challenging. Various interesti
arXiv:2610.18787v1 Announce Type: cross Abstract: Existing malware detection approaches heavily rely on handcrafted features derived from static or dynamic analysis of the executable files. These meth