Knowledge catalogue
arXiv:2609.23333v1 Announce Type: new Abstract: Digital direct-to-consumer (DTC) health campaigns are usually measured after the fact. In-flight forecasting commonly relies on a separate classifier fo
arXiv:2609.22194v1 Announce Type: new Abstract: Enterprise analytics agents solve long-horizon tool-use problems over distributed business data, requiring retrieval, reasoning, API calls, code executi
arXiv:2609.24205v1 Announce Type: cross Abstract: Modern AI model training imposes unprecedented computational demands, making it a key contributor to datacenter energy consumption. Yet a significant
arXiv:2510.02538v2 Announce Type: replace Abstract: We are interested in solving the problem of imitation learning with a limited amount of real-world expert data. Existing offline imitation methods o
arXiv:2609.22871v1 Announce Type: new Abstract: In-hand assembly is constrained by the need to maintain grasps on two separate parts while controlling their relative motion within a single hand. To en
arXiv:2606.18193v2 Announce Type: replace-cross Abstract: We evaluate the adversarial robustness of three frontier large language models (LLMs) developed by Anthropic, Opus 4.8, Fable 5 and its succes
arXiv:2609.22109v1 Announce Type: new Abstract: Selective on-policy distillation trains a student only at the token positions a selector scores highest, and the literature compares selectors under a s
arXiv:2601.12538v2 Announce Type: replace-cross Abstract: Reasoning is a fundamental cognitive process underlying inference, problem-solving, and decision-making. While large language models (LLMs) de
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:2609.22229v1 Announce Type: new Abstract: We generated synthetic multivariate time series for 27 refrigerators with a simplified physicsinspired simulator at one-minute resolution. The simulator
arXiv:2609.24467v1 Announce Type: new Abstract: Music festival lineups emerge from complex relationships among artists, genres, releases, labels, and past performances, making the prediction of future
arXiv:2609.24189v1 Announce Type: new Abstract: Vision-language navigation requires embodied agents to navigate environments using natural language instructions and visual observations. Existing appro
arXiv:2411.15921v3 Announce Type: replace Abstract: The removal of multiplicative Gamma noise is a critical research area in the application of synthetic aperture radar (SAR) imaging, where neural net
arXiv:2609.22249v1 Announce Type: new Abstract: This paper treats prompt engineering as a discipline for turning informal human intent into structured AI work specifications. It develops the practice
arXiv:2602.02940v2 Announce Type: replace-cross Abstract: Formal semantics and distributional semantics are distinct approaches to linguistic meaning: the former models meaning as reference via model-
arXiv:2609.24098v1 Announce Type: new Abstract: Visual Question Answering (VQA) with Multimodal Large Language Models (MLLMs) requires not only producing safe and effective responses, but also groundi
arXiv:2609.24702v1 Announce Type: new Abstract: We study scalable peer-to-peer dynamic average consensus (DC) for multi-robot systems under finite-range, finite-rate, and interference-constrained comm
arXiv:2510.11676v2 Announce Type: replace-cross Abstract: We study convex composite optimization problems, where the objective function is given by the sum of a prox-friendly function and a convex fun
arXiv:2609.24150v1 Announce Type: new Abstract: Speculative decoding accelerates large language model (LLM) inference by using a lightweight draft model to generate multiple candidate tokens that are
arXiv:2601.03679v2 Announce Type: replace-cross Abstract: Decarbonization of isolated or off-grid energy systems through phase-in of large shares of intermittent solar or wind generation requires co-i
arXiv:2609.23408v1 Announce Type: new Abstract: In frame interpolation tasks, motion ambiguity in the training set causes models to generate blurry intermediate frames. Moreover, the assumption of uni
arXiv:2609.24127v1 Announce Type: new Abstract: Atomic activity understanding aims to recognize and localize structured traffic behaviors that jointly encode motion patterns and their grounding in roa
arXiv:2609.23836v1 Announce Type: new Abstract: A fundamentally challenging question in K-12 education is about the effects of taking more advanced or challenging classes. It is particularly complex b
arXiv:2609.22385v1 Announce Type: cross Abstract: Achieving high task success and efficiency remains a central pursuit in embodied exploration. Existing frameworks typically guide agent behavior throu
arXiv:2609.24565v1 Announce Type: new Abstract: Architectural drawings encode material classes through repeated hatch patterns. We test whether a connectome-constrained fly visual network, pretrained
arXiv:2609.24124v1 Announce Type: new Abstract: Active perception and manipulation are crucial for robots to interact with complex scenes. Existing benchmarks struggle to evaluate how robots effective
arXiv:2603.11984v2 Announce Type: replace Abstract: Diffusion-based visuomotor policies model complex action distributions through iterative denoising, but repeated inference adds latency to robotic c
arXiv:2606.15080v2 Announce Type: replace Abstract: While Large Reasoning Models (LRMs) show strong performance in English, they often fail to reason in the language of the query, a phenomenon known a
arXiv:2609.22100v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) improves language models with retrieved evidence, but processing many long passages is costly and can introduce dis
arXiv:2609.22562v1 Announce Type: new Abstract: Multi-vector visual document retrieval (VDR) models such as ColPali and ColNomic achieve strong accuracy by representing each document with hundreds to
arXiv:2609.24302v1 Announce Type: cross Abstract: Virtual screening aims to prioritize active compounds from large chemical libraries within a limited experimental budget. When applying Boltz-2 to vir
arXiv:2609.24698v1 Announce Type: new Abstract: Repeated execution of the target model during autoregressive decoding is a major source of LLM inference latency. Unlike linear speculation, which follo
arXiv:2609.24109v1 Announce Type: new Abstract: Zero-shot brain-to-image retrieval requires robust alignment between noisy EEG responses and visual representations. Existing EEG-vision alignment metho
arXiv:2609.23843v1 Announce Type: new Abstract: Scheduling clients for model training is critical in federated learning due to both data and system heterogeneity. Most previous works focus on the qual
arXiv:2609.24233v1 Announce Type: new Abstract: Electroencephalography (EEG) provides non-invasive monitoring of brain activity and is widely used in emotion recognition, motor imagery and sleep stagi
arXiv:2609.22185v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) provide a mesh-free approach for solving differential equations, but their performance can depend strongly on l
arXiv:2503.03370v3 Announce Type: replace Abstract: Cross-domain cell detection for microscopic images suffers from performance degradation due to distribution shifts across imaging domains. Unsupervi
arXiv:2609.24260v1 Announce Type: cross Abstract: We study the problem of adversarially robust PAC learning. In this framework, the learner observes independent samples from an unknown distribution ov
arXiv:2609.22332v1 Announce Type: cross Abstract: Generalizable robot manipulation requires predicting how a scene will evolve, identifying where interactions are feasible, and determining how to act.
arXiv:2609.22951v1 Announce Type: cross Abstract: Enterprise agentic systems that route every trajectory step to a frontier model waste 60-80% of their inference budget on subtasks that smaller models
arXiv:2609.24487v1 Announce Type: new Abstract: In this work, we present a method for shape reconstruction and tracking from video via agentic analysis-by-synthesis. Unlike prior methods which first e
arXiv:2609.22096v1 Announce Type: new Abstract: Climate campaigns are often evaluated through attention and mobilization, but less is known about the well-being language that accompanies them. Whether
arXiv:2609.23084v1 Announce Type: new Abstract: Over-the-air federated learning lets edge devices transmit their local updates simultaneously, reducing the communication overhead. The resulting wavefo
arXiv:2609.22796v1 Announce Type: new Abstract: Dialectal Arabic machine translation (MT) remains challenging despite recent progress in Arabic language technologies, particularly because effective tr
arXiv:2609.23478v1 Announce Type: new Abstract: Latent action models infer a code for the transition between two frames of action-free video. Recent methods regularise this code to compose additively
arXiv:2609.22757v1 Announce Type: cross Abstract: A (coarse) correlated equilibrium (CE) is information-value-free (IVF) if a player can match the payoff obtained from recommendations by committing to
arXiv:2609.24330v1 Announce Type: new Abstract: Image morphing aims to produce a smooth and semantically consistent transition between two input images. Existing diffusion-based morphing methods eithe
arXiv:2609.24058v1 Announce Type: new Abstract: Multilingual scene text recognition (STR) remains challenging due to the scarcity of training data for most languages and the difficulty of serving dive
arXiv:2505.18918v4 Announce Type: replace-cross Abstract: Principal component analysis (PCA) is a key tool in the field of data dimensionality reduction. Various methods have been proposed to extend P
arXiv:2609.22323v1 Announce Type: new Abstract: Few-shot learning research is predominantly evaluated on accuracy alone, with limited attention to the parameter and training-sample budgets required to
arXiv:2609.22277v1 Announce Type: cross Abstract: Visual impairment affects over 2.2 billion people worldwide, yet conventional white canes cannot detect elevated hazards or provide semantic environme
arXiv:2609.23586v1 Announce Type: new Abstract: The rapid development of video generative models (VGMs) has enabled the generation of highly realistic synthetic videos, raising concerns about the inte
arXiv:2609.22114v1 Announce Type: new Abstract: Context compression is widely proposed as a way to cut the token bill of LLM coding agents, and public benchmarks report that aggressive compression pre
arXiv:2609.22973v1 Announce Type: new Abstract: Adapting a pretrained Vision-Language-Action (VLA) model to a new robot, environment, or task requires demonstrations that are collected locally and oft
arXiv:2602.04068v2 Announce Type: replace Abstract: The calculation of shortest-path distances in road networks is a core operation in navigation systems, location-based services, and spatial analytic
arXiv:2609.23161v1 Announce Type: new Abstract: A conventional camera uses millions of pixels to measure radiance from all directions within its field of view. We present an omnidirectional irradiance
arXiv:2609.22942v1 Announce Type: new Abstract: Generative models are rapidly expanding image quality assessment (IQA) beyond traditional fidelity factors to emerging dimensions such as physical plaus
arXiv:2609.24741v1 Announce Type: new Abstract: We develop an exact linear programming (LP) formulation for bounded-depth classification trees with binary features, using a junction-tree representatio
arXiv:2609.22917v1 Announce Type: new Abstract: Non-technical stakeholders frequently cannot write the SQL needed to extract insights from operational databases. We built and evaluated a Text-to-SQL a
arXiv:2609.23097v1 Announce Type: cross Abstract: Internet of Things (IoT) systems are increasingly deployed in smart homes, transportation, energy systems, and critical infrastructure. This broad con