Knowledge catalogue
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:2609.31653v1 Announce Type: cross Abstract: Sentiment analysis is a common tool for converting unstructured text into quantitative signals in finance and risk management. Yet most applications r
Dots will be available in ChatGPT on web, mobile, and desktop across Pro, Business Premium, and Enterprise users in eligible markets. To get started, create your first dot in the ChatGPT desktop app o
arXiv:2609.33530v1 Announce Type: cross Abstract: Natural Language Understanding (NLU) plays a crucial role in various applications, yet its performance suffers from weaknesses in handling the complex
arXiv:2609.34346v1 Announce Type: new Abstract: Temporally dense optical flow is essential for dynamic perception in immersive VR/AR systems, where rapid head, hand, and object motion must be continuo
arXiv:2507.21616v3 Announce Type: replace Abstract: We study the output representation of a neural network used for next event prediction. We propose partitioning the time axis into a fixed set of int
arXiv:2609.31804v1 Announce Type: cross Abstract: Space weather disturbances driven by the solar wind can degrade satellite navigation, disrupt radio communications, and threaten power infrastructure,
EliseAI, a startup that develops artificial intelligence tools for real-estate companies and healthcare providers, has raised 350 million in funding. Andreessen Horowitz and Bessemer jointly led the r
arXiv:2609.33758v1 Announce Type: new Abstract: Reliable document digitization in uncontrolled capture settings is challenging because real images exhibit multiple interacting degradations rather than
arXiv:2601.22944v3 Announce Type: replace Abstract: Out-of-distribution generalization becomes challenging when spurious correlations vary across environments while difficult or underrepresented sampl
arXiv:2510.04979v2 Announce Type: replace Abstract: Receiver Operating Characteristic (ROC) and Precision-Recall (PR) curves are fundamental analytical tools for evaluating classification models, prov
arXiv:2609.33167v1 Announce Type: new Abstract: We present FloodDiffusion 2 (FD2), an efficient and controllable framework that builds upon FloodDiffusion (FD1), a state-of-the-art streaming motion ge
arXiv:2609.34149v1 Announce Type: new Abstract: Current methods for egocentric view action recognition often face challenges in perceiving dynamic hand movements relying solely on geometrical or physi
arXiv:2609.35770v1 Announce Type: new Abstract: Realistic and editable animal fur reconstruction from multi-view images is challenging due to fine-scale detail, self-occlusion and obfuscation, and, un
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 has released GPT‑6.1 Sol, which becomes available immediately for all Plus, Pro, Business, Enterprise, and Educational plan users within ChatGPT Work and Codex. The announcement was posted on O
arXiv:2609.32365v1 Announce Type: new Abstract: Dense associative memories have traditionally focused on storing and retrieving vector-valued patterns. Many modern machine learning problems, however,
arXiv:2508.14859v2 Announce Type: replace Abstract: Temporal graph learning is crucial for dynamic networks where nodes and edges evolve over time and new nodes continuously join the system. Inductive
arXiv:2511.02468v2 Announce Type: replace-cross Abstract: Mobile eye-tracking is crucial for capturing human visual attention in real-world and XR settings, supporting research and human-computer inte
arXiv:2505.17458v3 Announce Type: replace Abstract: Machine learning on heterogeneous graphs has advanced rapidly, driven by the diverse entities, relations, and semantics inherent in real-world data.
arXiv:2609.34670v1 Announce Type: cross Abstract: In this paper, we propose a representation of a digraph (directed graph) as a Hermitian matrix derived from its adjacency matrix. This representation
arXiv:2609.32008v1 Announce Type: new Abstract: Recent advances in sensor technology have enabled more effective human activity recognition (HAR), particularly in real-time systems with limited comput
arXiv:2609.31840v1 Announce Type: new Abstract: High-speed racket sports provide a demanding testbed for humanoid robots, requiring time-critical decisions, precise striking, and dynamic whole-body co
arXiv:2609.33096v1 Announce Type: new Abstract: Rapid advances in humanoid robotics have motivated growing interest in the application of humanoids for healthcare and clinical tasks. However, it remai
arXiv:2609.34584v1 Announce Type: cross Abstract: In-game toxic language has emerged as a critical concern in the gaming industry and community. While several frameworks and models for online game tox
arXiv:2609.33523v1 Announce Type: new Abstract: We present In-Token Learning, an image restoration framework that adapts a pretrained diffusion transformer using conditional rectified flow matching. C
arXiv:2609.31665v1 Announce Type: new Abstract: Action anticipation predicts future human actions from partial video under incomplete context and temporal uncertainty. Recent systems introduce large l
arXiv:2509.01135v3 Announce Type: replace Abstract: Electroencephalography (EEG)-based emotion recognition plays a critical role in affective Brain-Computer Interfaces (aBCIs), yet its practical deplo
arXiv:2606.15685v2 Announce Type: replace-cross Abstract: Embodied Continual Learning (ECL) aims to enable robots to continually acquire new manipulation tasks while retaining previously learned behav
arXiv:2510.02284v4 Announce Type: replace Abstract: Recent video generation models have achieved remarkable progress and are now deployed in film, social media production, and advertising. Beyond thei
arXiv:2609.31806v1 Announce Type: new Abstract: Accurate medium-term, from a few months to a few years, electricity load forecasts are crucial for informed decision-making in power plant maintenance s
arXiv:2609.35652v1 Announce Type: new Abstract: Mobile manipulation extends robot interaction beyond a fixed kinematic workspace by making the reachable region itself controllable. This flexibility in
arXiv:2609.33232v1 Announce Type: new Abstract: Continuous-time sensing and monitoring with timely and accurate decision-making are critical for many real-world applications. In healthcare monitoring
arXiv:2609.33174v1 Announce Type: new Abstract: Advancing bipedal robots to navigate diverse terrains remains a significant challenge in robotics. Traditional locomotion controllers excel on specific
arXiv:2609.32302v1 Announce Type: new Abstract: Prompt engineering has become an indispensable tool for using large language models (LLMs), turning LLMs into task-specific experts without changing the
arXiv:2505.11840v4 Announce Type: replace Abstract: As the default optimizer for training large language models, AdamW has achieved remarkable success in deep learning. However, its convergence behavi
Kris Holt / Engadget: OpenAI announces ChatGPT Space, a collaborative hub for shared pages and files, available on Pro, Business, and Enterprise plans; it replaces Library — ChatGPT is coming to Slack
arXiv:2609.34759v1 Announce Type: new Abstract: Recent vision-language models (VLMs) have advanced vision-and-language navigation (VLN), enabling models to predict navigation actions from visual obser
arXiv:2609.31716v1 Announce Type: new Abstract: Persistent semantic occupancy mapping is essential for embodied scene understanding. However, perspective-based systems provide limited spatial coverage
arXiv:2609.34795v1 Announce Type: new Abstract: Underwater image enhancement is crucial for improving visual perception in marine applications. Existing underwater image enhancement studies mainly foc
arXiv:2609.32465v1 Announce Type: new Abstract: Decision-focused learning (DFL) trains predictors for downstream decision quality, but often relies on optimal reference decisions that are expensive to
arXiv:2609.32741v1 Announce Type: new Abstract: Modern semiconductor production relies on a globally distributed, multi-tier supply chain in which financial stress at one firm spreads with a delay and
arXiv:2609.31912v1 Announce Type: new Abstract: Strongly paired medical image translation contains a substantial component that can be predicted directly from the source. The current reality is that p
arXiv:2609.34120v1 Announce Type: new Abstract: The majority of research on electricity consumption forecasting has focused on deterministic approaches, which generate a single point estimate for each
arXiv:2603.18095v2 Announce Type: replace Abstract: Post-training quantization (PTQ) is a practical path to deploy large diffusion models, but quantization noise can accumulate over the denoising traj
arXiv:2609.35094v1 Announce Type: new Abstract: Uncrewed aerial manipulators (UAMs) integrate robotic arms with aerial platforms for three-dimensional physical interaction. However, enlarging the work
arXiv:2609.34680v1 Announce Type: new Abstract: Four-bit post-training quantization can reduce the memory demands of large language models, but preserving accuracy under strict MXFP4 W4A4 requires coo
arXiv:2609.33340v1 Announce Type: new Abstract: Contextual specialization can improve forecasting accuracy, but a correction selected on one historical interval may become unreliable under temporal di
arXiv:2609.34170v1 Announce Type: new Abstract: Flow-based vision-language-action (VLA) models are highly effective for generalist robot manipulation, yet their reliance on computationally expensive V
arXiv:2609.33065v1 Announce Type: cross Abstract: Large language model (LLM) assistants can now search the web and consult external sources while completing user requests. These sources can provide us
arXiv:2505.09274v2 Announce Type: replace Abstract: Medical imaging is a cornerstone of modern healthcare, driving advancements in diagnosis, treatment planning, and patient care. Among its various ta
arXiv:2609.35075v1 Announce Type: new Abstract: Many sensing tasks obtain training labels only by deploying instruments in the field. With a limited number of sensor kits, a collection deadline, and m
arXiv:2609.33020v1 Announce Type: new Abstract: Diffusion models achieve state-of-the-art results across multiple tasks. However, in inverse problems, standard initialization from pure Gaussian noise
arXiv:2609.35469v1 Announce Type: cross Abstract: Autoregressive Vision-Language-Action (VLA) models offer a scalable path to robot learning, yet existing action tokenizers treat tokenization as a com
arXiv:2609.32250v1 Announce Type: new Abstract: Sign-language interpretation in public communication relies on qualified professional interpreters and can be difficult to scale, motivating robotic sig
arXiv:2609.32500v1 Announce Type: new Abstract: Many real-world time series data exhibit structural properties at multiple scales, from short, recurring units to complex sequences composed of these un
arXiv:2410.02331v3 Announce Type: replace Abstract: The increasing demand for transparent and reliable models, particularly in high-stakes decision-making areas such as medical image analysis, has led
arXiv:2609.31801v1 Announce Type: new Abstract: Complex systems such as vehicles, patients, or genomes emit discrete event sequences whose operative question is causal, not predictive: which events ca
arXiv:2609.32676v1 Announce Type: new Abstract: Time Series Foundation Models (TSFMs) have achieved remarkable zero-shot performance through extensive pre-training on massive time series datasets. Nev
arXiv:2609.31940v1 Announce Type: new Abstract: Multi-objective Bayesian optimization (MOBO) is commonly approached through specialized acquisition functions or scalarization schemes designed to expli