Knowledge catalogue
arXiv:2609.16680v1 Announce Type: new Abstract: Manufacturing consumes one third of global energy and still has significant room for improvement in terms of energy efficiency. Optimal process control
arXiv:2609.16161v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown impressive capabilities across a range of natural language processing tasks, and LLM inference has emerged as a
arXiv:2609.16155v1 Announce Type: cross Abstract: This paper presents a novel framework leveraging Large Language Models (LLMs) to generate synthetic time series data for manufacturing processes. Moti
arXiv:2609.16033v1 Announce Type: cross Abstract: Cervical vertebral maturation (CVM) assessment plays a pivotal role in orthodontic diagnosis and determining the optimal timing of treatment, especial
arXiv:2609.16051v1 Announce Type: cross Abstract: Semantic collapse, the progressive narrowing of what AI systems generate, has been studied mainly in closed settings, and remedies have targeted model
arXiv:2609.17184v1 Announce Type: cross Abstract: Looped Transformers achieve strong performance with compact parameter sizes by repeatedly applying a shared stack of Transformer blocks across recurre
arXiv:2609.17124v1 Announce Type: new Abstract: Offshore maintenance requires operations in the air, the surface, and the subsea domain and include human supervision. This paper presents LOTUSim-Energ
arXiv:2609.16730v1 Announce Type: new Abstract: Conversational memory changes during use, so endpoint question answering alone cannot establish how a persistent state accumulates, ages, or incorporate
As enterprise organizations scale mission-critical applications, storage I/O and memory access can become severe operational bottlenecks. Whether its Oracle databases, in-memory databases like SAP HAN
arXiv:2609.17300v1 Announce Type: cross Abstract: Artificial ontogeny, developmental encodings, robot reproduction, and inherited controllers are established research directions, yet a narrower questi
arXiv:2609.16695v1 Announce Type: new Abstract: Large-scale pre-training has transformed representation learning in 2D vision, yet its transferability to 3D single object tracking (SOT) remains insuff
arXiv:2609.16056v1 Announce Type: cross Abstract: Humans carry behaviour knowledge of how to act in familiar situations into every new task rather than relearning it from scratch. There is no reason a
arXiv:2609.16331v1 Announce Type: new Abstract: We present ManiSkillFormer, a neuro-symbolic framework for demonstration-free and compositional robotic manipulation. Instead of learning end-to-end vis
arXiv:2609.16260v1 Announce Type: cross Abstract: Artificial intelligence (AI) poses different levels of risk across sectors, but are these differences reflected in U.S. federal AI governance? To help
arXiv:2609.16475v1 Announce Type: new Abstract: Multi subject video editing modifies designated subjects while preserving non target content, but faces cross subject attribute leakage, and occlusion a
arXiv:2609.16004v1 Announce Type: cross Abstract: While AI systems increasingly shape high-stakes societal domains, their governance is limited by the lack of risk management methods that operate on r
arXiv:2609.16859v1 Announce Type: new Abstract: To train handwritten text recognition systems we need word images and their corresponding transcriptions, and these transcriptions are produced manually
arXiv:2606.19469v2 Announce Type: replace Abstract: Undergraduate computer science is governed by international curricular guidelines revised about once a decade, yet programs lack a reliable way to m
arXiv:2408.14792v4 Announce Type: replace-cross Abstract: With the growing prevalence of generative artificial intelligence (AI), an increasing amount of content is no longer exclusively generated by
arXiv:2609.16012v1 Announce Type: new Abstract: Despite significant progress in general visual question answering and cross-modal understanding, multimodal large language models still face a pronounce
arXiv:2609.16934v1 Announce Type: new Abstract: Cranial implant generation is an important task in medical imaging. Recent point cloud based generative methods, particularly flow matching, offer stron
arXiv:2609.16684v1 Announce Type: new Abstract: Learning manipulation from human video requires high-fidelity hand-motion reconstruction in metric units. Today's metric hand labels come from studio ri
arXiv:2606.18960v3 Announce Type: replace Abstract: Action-conditioned world models have emerged as a promising paradigm for robot learning, offering a scalable alternative to costly real-world experi
arXiv:2609.17223v1 Announce Type: new Abstract: Medical AI models hold immense potential to improve patient outcomes, but they are also known to unintentionally memorise individual records from their
arXiv:2602.00532v2 Announce Type: replace-cross Abstract: Constraint handling is central to constrained black-box optimization (BBO), where objective improvement and feasibility restoration often prov
arXiv:2609.16245v1 Announce Type: new Abstract: Long-horizon scientific discovery requires agents to alternate between exploration, disciplined execution, and critical reassessment as evidence changes
arXiv:2505.24846v3 Announce Type: replace Abstract: Reward modeling is a key step in building safe foundation models when applying reinforcement learning from human feedback (RLHF) to align Large Lang
arXiv:2602.08776v2 Announce Type: replace Abstract: Contact-rich teleoperation logs expose a policy I/O design choice: demonstrations may contain the robot execution (E), leader command (C), or both.
arXiv:2609.16365v1 Announce Type: cross Abstract: Real-world datasets often exhibit long-tailed class distributions, where a few head classes contain a large number of training samples while a large n
We gave two small LLMs a real customer-service task. One got 100/100. The other stopped with the job half-done. I wanted to test something more meaningful than benchmark scores: can a small model actu
A follow-up to my earlier post about small models on phones. Last time it was fixed tasks in a single browser. This is something else. Ministral 3 3B Q4_K_M in llama.cpp on a Samsung Galaxy S21, four
Latest version of the benchmark introduces two new tests for emerging AI deployment patterns, including Agentic Inference The post MLCommons Sets Participation Record with New MLPerf Inference v6.1 Be
MLPerf Inference v6.1 introduced the first agentic workload run on datacenter hardware and evaluated a model with more than one trillion parameters (Kimi K2), setting a new benchmark for scale. The te
arXiv:2609.17306v1 Announce Type: cross Abstract: Multi-agent Systems (MAS) combine multiple model outputs to solve complex reasoning tasks. However, despite rapid growth of available open-source mode
arXiv:2609.17180v1 Announce Type: new Abstract: Multimodal counselor response generation (MCRG) aims to generate an appropriate counselor response from multimodal dialogue histories. Progress is limit
arXiv:2609.17524v1 Announce Type: new Abstract: World-action models (WAMs) jointly model future observations and actions, typically predicting the future as RGB images. Other visual modalities such as
arXiv:2609.16252v1 Announce Type: cross Abstract: Machine-readable models such as SysML v2 are now programmatically accessible, and a growing body of work treats that access as the enabling condition
arXiv:2609.16028v1 Announce Type: cross Abstract: Designing polymers with targeted properties requires navigating vast chemical spaces from limited labeled data. Here we introduce PolyLatentFlow, a fr
arXiv:2609.16810v1 Announce Type: new Abstract: The exploration of high-dimensional spaces remains a challenging problem, in particular in the presence of narrow passages and small clearances. We prop
arXiv:2609.16041v1 Announce Type: new Abstract: Visual torque feedback supports underwater bilateral teleoperation, but the benefit of mixed reality (MR) over conventional monitor presentation remains
arXiv:2603.11515v2 Announce Type: replace Abstract: Today's scientific challenges, from climate modeling to Inertial Confinement Fusion design to novel material design, require exploring huge design s
arXiv:2609.16917v1 Announce Type: cross Abstract: Multilayer Artificial Neural Networks trained via backpropagation are the basic blocks of many, more complex, classification algorithms. Their strengt
arXiv:2609.16347v1 Announce Type: new Abstract: Sea-ice type prediction is important for climate monitoring, maritime navigation, and decision-making in polar regions. The main source of label data fo
arXiv:2609.16875v1 Announce Type: new Abstract: Upgrading embedding models typically requires expensive database re-indexing, as new query embeddings are incompatible with existing database embeddings
arXiv:2512.15708v2 Announce Type: replace Abstract: Foundation models are vital tools in various Computer Vision applications. They take as input a single RGB image and output a deep feature represent
arXiv:2609.17181v1 Announce Type: cross Abstract: The analysis and classification of cultural heritage architectural styles remain challenging due to the complexity of visual images of buildings, whic
arXiv:2609.16168v1 Announce Type: cross Abstract: Working agricultural landscapes are often treated as background to wildfire disasters, even though they are managed fuel mosaics, productive assets, a
arXiv:2609.17169v1 Announce Type: cross Abstract: Forecasting anatomical changes such as tumor growth and neurodegeneration is a challenging generative vision task. Morphological evolution is subtle r
arXiv:2609.16090v1 Announce Type: cross Abstract: Music retrieval is relation-dependent: given a reference track, a listener may seek its style with a new theme, a cover, or a comparable voice, and th
My name is Chris Painter, and I'm the President of METR (Model Evaluation and Threat Research). I know we've made a lot of new friends on the internet the last couple of days, so I thought I'd take th
arXiv:2609.17194v1 Announce Type: new Abstract: High-density surface electromyography (HD-sEMG) gesture recognition supports prosthetic control, assistive robotics, and rehabilitation, but electrode r
arXiv:2609.16984v1 Announce Type: new Abstract: Open-weight language models publish the strings their chat templates use to mark turns, roles and tool results, which the tokenizer maps back to the res
arXiv:2609.16294v1 Announce Type: cross Abstract: Tracking the energy transition requires reliable statistics on renewable deployment. Rooftop photovoltaics (PV) are especially hard to track, owing to
arXiv:2609.17048v1 Announce Type: cross Abstract: We study nonconvex methods for matrix completion, the problem of recovering a low-rank matrix from a subset of its entries. Convex methods achieve sam
arXiv:2609.16396v1 Announce Type: new Abstract: Negation is typically modeled through its linguistic realization, although spoken interaction is accompanied by tightly coordinated nonverbal behavior.
arXiv:2609.16010v1 Announce Type: new Abstract: The complexity of legal language and limited accessibility to legal information pose significant challenges to justice delivery in Nepal. Traditional le
arXiv:2609.15999v1 Announce Type: new Abstract: Accessing legal information in Nepal is difficult due to complex terminology, limited resources, and misinformation. We introduce an AI-powered legal as
arXiv:2609.17160v1 Announce Type: new Abstract: Machine-learning surrogate models offer a promising alternative to high-fidelity Computational Fluid Dynamics (CFD) simulations for aerodynamic analysis
arXiv:2609.17064v1 Announce Type: new Abstract: Assistive autonomous systems must anticipate human goals before an observed behavior is complete. This article formulates anticipation as goal inference
arXiv:2602.10480v4 Announce Type: replace Abstract: Large language models (LLMs) exhibit strong general-purpose reasoning capabilities, yet they frequently hallucinate when used as world models (WMs),