Knowledge catalogue
arXiv:2608.22364v1 Announce Type: new Abstract: World action models (WAMs) couple visual future prediction with robot action generation, but accelerated students can lose task capabilities during dist
arXiv:2608.22859v1 Announce Type: cross Abstract: RAG systems are increasingly used to summarize what large collections of documents say. A user asks 'What do people think about X?' and receives an an
arXiv:2608.21369v1 Announce Type: cross Abstract: Nigerian Pidgin is one of Africa's most widely spoken languages, yet remains severely underrepresented in language model evaluation. Existing benchmar
arXiv:2608.22584v1 Announce Type: new Abstract: Two-stage neuro-symbolic architectures provide an elegant paradigm for visual problem solving by cleanly separating connectionist perception of predefin
arXiv:2608.22110v1 Announce Type: new Abstract: We ask what gets a language model onto the Apple Neural Engine (ANE) and what makes it fast there, and we answer with three measurements. We sweep a 64-
arXiv:2608.22614v1 Announce Type: new Abstract: Interpretability research increasingly asks when concepts emerge during training and whether linear probes recover real structure, but in language model
arXiv:2608.22985v1 Announce Type: new Abstract: Activation steering is often evaluated under the answer encoding used to construct the direction. A reported gain may reflect the intended judgment or c
arXiv:2608.21761v1 Announce Type: new Abstract: Large collections of street-view imagery provide rich visual information about urban environments, but extracting fine-grained geographic information fr
arXiv:2009.09083v4 Announce Type: replace-cross Abstract: The term intelligent system has emerged in the field of information technology as a category of computer systems derived from successful appli
arXiv:2608.23218v1 Announce Type: new Abstract: Advances in neural theorem provers have been impressive, but the successes obscure a broader vision of what AI can do for mathematics and how mathematic
arXiv:2608.22507v1 Announce Type: new Abstract: Long jumpers with below the knee amputation (BKA) that take off from their running-specific prosthesis (RSP) improved performances significantly over th
arXiv:2608.23295v1 Announce Type: new Abstract: Memory-based anomaly detectors store nominal training patches and score test patches against this memory. A patch selected for coverage therefore become
arXiv:2604.05779v2 Announce Type: replace-cross Abstract: While large language models (LLMs) demonstrate strong capabilities across diverse user queries, they still suffer from hallucinations, often a
arXiv:2608.21523v1 Announce Type: cross Abstract: One aim of neural network field theory is to put a quantum or effective field theory on a computer, with the network ensemble itself as the theory. We
arXiv:2608.22960v1 Announce Type: new Abstract: Coding agents are increasingly evaluated not only by whether they solve a task, but also by how they execute it. However, existing process-level evaluat
arXiv:2608.22948v1 Announce Type: cross Abstract: Large language models are increasingly used to propose research ideas, yet the prevailing ways of judging such ideas supply no shared decision rule: f
arXiv:2608.23299v1 Announce Type: new Abstract: Memory-based anomaly detectors store nominal training patches and score test patches against this memory. A patch selected for coverage therefore become
arXiv:2608.23474v1 Announce Type: cross Abstract: Vision-language models (VLMs) achieve strong performance on video and image-sequence benchmarks, yet it remains unclear whether they capture temporal
arXiv:2608.23075v1 Announce Type: cross Abstract: Learned surrogates for expensive inner solver blocks are a widely pursued route to faster multiphysics simulation. We report a controlled, end-to-end
arXiv:2608.22366v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly being used for document understanding, yet their role in Arabic and Islamic manuscript recognition remain
arXiv:2608.22504v1 Announce Type: new Abstract: Existing AI-for-PDE benchmarks primarily assess models in terms of predictive or approximation accuracy. In physics research, however, AI outputs often
arXiv:2608.22174v1 Announce Type: new Abstract: Unified multimodal models (UMMs) can perform both understanding and generation, raising a central question: can visual generation improve understanding?
arXiv:2608.23161v1 Announce Type: new Abstract: Heavy-duty vehicle diagnostics generate three disconnected data modalities: unstructured multi- lingual service complaints, high-dimensional sensor tele
arXiv:2608.22082v1 Announce Type: new Abstract: Patch-memory anomaly detectors assume that their reference bank is normal, an assumption that is difficult to guarantee when additional industrial image
arXiv:2608.23507v1 Announce Type: cross Abstract: Historical people may appear under different languages, scripts, and transcription traditions, while distinct individuals may share highly similar or
arXiv:2608.22339v1 Announce Type: new Abstract: Extracting skills from past successes is critical for the efficient evolution of Large Language Model (LLM) agents. Prevailing agent self-evolution para
arXiv:2608.22438v1 Announce Type: new Abstract: Persona-conditioned large language models (LLMs) are increasingly used to simulate survey responses across diverse domains. However, apparent response v
arXiv:2608.22233v1 Announce Type: cross Abstract: Test-time adaptation (TTA) aims to improve model robustness under distribution shift by adapting a source model using unlabeled test data. Although me
arXiv:2608.23024v1 Announce Type: new Abstract: Counterfactual medical image generation aims to modify an existing image to reflect a hypothetical scenario in which certain characteristics of the imag
arXiv:2608.22347v1 Announce Type: new Abstract: A cognitive architecture is more than the module that reasons: it must also decide how long to think and what deserves the effort. We built a minimal bu
arXiv:2608.22421v1 Announce Type: new Abstract: World models predict action-conditioned futures and serve as critical internal simulators for downstream planning and control. However, catastrophic pre
arXiv:2602.13106v2 Announce Type: replace-cross Abstract: In recent years, there has been growing interest in understanding neural architectures' ability to learn to execute discrete algorithms, a lin
arXiv:2608.23221v1 Announce Type: cross Abstract: Historical retrieval for time-series prediction commonly treats past similarity as a proxy for usefulness. We ask a different question: which historic
arXiv:2608.22230v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for hate speech moderation, often within human--AI workflows in which reviewers provide feedback befo
arXiv:2608.22490v1 Announce Type: new Abstract: Safety alignment helps models adhere to human values, but it often reduces response utility. We ask a critical but understudied question: Does safety al
arXiv:2608.22127v1 Announce Type: new Abstract: Text-Attributed Graphs (TAGs) integrate graph structures and node-associated textual attributes, and recent studies have increasingly leveraged Large La
arXiv:2508.09846v2 Announce Type: replace Abstract: This paper presents an object-aware whole-body bilateral teleoperation framework for wheeled humanoid loco-manipulation. This framework combines who
arXiv:2608.22155v1 Announce Type: cross Abstract: The study of adversarial examples and their origins remains an open area of research. Mechanistic interpretability, and superposition in particular, o
arXiv:2608.21620v1 Announce Type: new Abstract: This paper investigates wearable-based recognition of human activities and gestures to support Human-Robot Interaction (HRI) in object-handover and asse
arXiv:2608.21662v1 Announce Type: cross Abstract: The topic of explanation in recommender systems has seen steady research attention since the earliest days of the field. With some exceptions, this wo
arXiv:2608.21752v1 Announce Type: new Abstract: It has long been known that well-trained neural networks can be compressed very strongly without affecting their performance, an important phenomenon th
arXiv:2608.22959v1 Announce Type: cross Abstract: While the top model on OmniDocBench now reaches 96.34% overall on printed-document parsing, the ability of current models to handle challenging handwr
arXiv:2608.22704v1 Announce Type: new Abstract: Long-form audio inputs make the KV cache the dominant memory cost of speech LLMs. Prefill-only KV compression methods permanently discard audio KV posit
arXiv:2608.21439v1 Announce Type: new Abstract: Game world models have recently demonstrated promising capabilities in generating visually coherent and action-controllable gameplay videos. However, no
arXiv:2608.22591v1 Announce Type: new Abstract: Robot policies receive heterogeneous observations at each decision step, yet sequence models differ in how they organize these inputs over time. We intr
arXiv:2602.13739v2 Announce Type: replace Abstract: Mobile robotic gas distribution mapping (GDM) provides critical situational awareness during emergency responses to hazardous gas releases. However,
arXiv:2608.22758v1 Announce Type: cross Abstract: Standard decoding rules for autoregressive language models promote diversity by rescaling the full next-token distribution or truncating its low-proba
arXiv:2601.15380v2 Announce Type: replace-cross Abstract: We generalize the attention mechanism by viewing it through the lens of Entropic Optimal Transport, revealing that standard attention correspo
arXiv:2608.22852v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used in investment decision-making, yet prior work shows that they exhibit systematic, model-specific inve
arXiv:2603.14254v2 Announce Type: replace Abstract: Test-time adaptation (TTA) aims to improve model robustness under distribution shifts by adapting to unlabeled test data, but most existing methods
arXiv:2608.20890v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have emerged as a powerful paradigm for end-to-end autonomous driving by jointly integrating perception, reasoning,
arXiv:2608.20980v1 Announce Type: new Abstract: Graph neural networks (GNNs) are routinely employed for short-range forecasting on multivariate time series with a spatial graph structure. Despite the
arXiv:2608.20608v1 Announce Type: new Abstract: Grape leaf disease recognition is important for precision agriculture, enabling early diagnosis, timely intervention, and improved vineyard management.
arXiv:2603.28200v2 Announce Type: replace-cross Abstract: Guiding collective motion in biological groups is a fundamental challenge in understanding social interaction rules. In this study, we propose
arXiv:2608.20394v1 Announce Type: cross Abstract: Industry pipelines that turn speech into supervised fine-tuning (SFT) data via multi-stage refinement are increasingly adopted but, to our knowledge,
arXiv:2608.20367v1 Announce Type: cross Abstract: Poultry production operates under tightly coupled environmental and biological dynamics, yet commercial climate control remains largely heuristic, lim
arXiv:2608.21140v1 Announce Type: cross Abstract: Reliable spatial understanding is an important prerequisite for future medical vision-language systems that aim to support radiological report generat
arXiv:2608.21186v1 Announce Type: new Abstract: Surgical procedures such as laparoscopic appendectomy are complex, high-stakes processes, yet formalizing their workflows for decision support remains a
arXiv:2608.20906v1 Announce Type: cross Abstract: The certification of Unmanned Aerial Vehicle (UAV) swarms for safety-critical operations requires verifiable design assurance. Airworthiness standards
arXiv:2608.20379v1 Announce Type: new Abstract: Advances in large language models (LLMs) have fueled a wave of research into agency: the ability to reason, plan, and act. This effort has produced agen