Knowledge catalogue
arXiv:2610.20560v1 Announce Type: cross Abstract: 3D object composition is pivotal to digital content creation and robot simulation, while also serving as a critical testbed for physical intelligence
arXiv:2610.18946v1 Announce Type: cross Abstract: Physical-layer spoofing attacks pose a critical threat to wireless localization systems by manipulating channel state information (CSI). Detecting suc
arXiv:2610.20524v1 Announce Type: new Abstract: Existing robot policy memories typically evolve with observation sequences, implicitly treating each update as the same amount of physical time. Yet ide
arXiv:2503.21821v2 Announce Type: replace Abstract: We introduce Physics, a benchmark for evaluating foundation models on advanced physics problem solving. It contains 1034 annotated, open-ended probl
arXiv:2610.18886v1 Announce Type: cross Abstract: Natural supercavitation behind conical cavitators generates a vapor-filled envelope that, when sustained over the full body of a high-speed underwater
arXiv:2610.19763v1 Announce Type: new Abstract: Physics-guided networks for underwater image restoration predict transmission and backscatter and invert the image-formation model, yet rarely test whet
arXiv:2506.20642v3 Announce Type: replace Abstract: Chain-of-Thought (CoT) prompting significantly enhances large language models' (LLMs) problem-solving capabilities, but still struggles with complex
arXiv:2610.20579v1 Announce Type: new Abstract: Unlike singles, humanoid table tennis doubles requires teammates to strike in strict alternation while sharing a confined workspace. Rapid repositioning
arXiv:2603.23678v2 Announce Type: replace Abstract: Large Language Models (LLMs) offer transformative solutions across many domains, but healthcare integration is hindered by strict data privacy const
arXiv:2606.22953v2 Announce Type: replace Abstract: Context managers summarize or evict old messages so agents can operate beyond a finite window. This creates a reliability problem: removing history
arXiv:2610.19131v1 Announce Type: cross Abstract: Maintenance work orders are the largest written record of how industrial equipment fails, yet in most plants they are close to unusable for analysis.
arXiv:2610.20584v1 Announce Type: new Abstract: Computer-use agents have demonstrated strong capabilities in interpreting screens and executing keyboard and mouse actions. However, games, with their v
arXiv:2610.19011v1 Announce Type: new Abstract: The Practical Molecular Optimization (PMO) benchmark standardized evaluation in molecular optimization, but it is built on simple property-based oracles
arXiv:2610.19605v1 Announce Type: cross Abstract: Long-output inference in large language models suffers from severe KV cache memory and bandwidth bottlenecks. While KV cache quantization alleviates t
arXiv:2610.19372v1 Announce Type: new Abstract: Runtime policy verifiers can prevent agents from executing disallowed actions, but their decisions are typically used only for enforcement and discarded
arXiv:2610.16145v1 Announce Type: new Abstract: Agent frameworks can persist checkpoints, trace tool calls, and limit resource use, but these facilities often assign different identities to execution,
arXiv:2610.19615v1 Announce Type: new Abstract: Reinforcement learning has enabled robust locomotion for legged robots, but learned policies are typically tied to a specific robot morphology and requi
arXiv:2409.00696v4 Announce Type: replace-cross Abstract: Rating-based human evaluation has become an essential tool to accurately evaluate the impressive performance of large language models (LLMs).
arXiv:2610.15969v1 Announce Type: new Abstract: In multi-agent reinforcement learning, exposing a cooperator to partners with diverse strategies during training is key to better collaboration at test
arXiv:2610.18917v1 Announce Type: cross Abstract: Urban venues such as restaurants, shops, bars and parks host the daily life of a city, and their collective rise and fall signals how vibrant a neighb
arXiv:2610.19143v1 Announce Type: new Abstract: While Vision-Language-Action models have enabled impressive cross-task transfer in zero-shot settings, adaptation methods are often necessary to achieve
arXiv:2610.20402v1 Announce Type: cross Abstract: Feldman's memorization lower bound assigns a frequency coefficient based on how often a point appears in the training sample. We give an exact three-p
arXiv:2610.14843v1 Announce Type: new Abstract: Claims of recursive self-improvement are easy to make and hard to falsify: did improvement come from re-using designer-provided mechanisms, or from mech
arXiv:2610.19048v1 Announce Type: new Abstract: Record linkage and demographic inference from names are routine demands in social science. Most approaches to these problems require labeled training da
arXiv:2610.18755v1 Announce Type: cross Abstract: Reinforcement learning (RL) from unit tests is the common recipe for post-training code models, but a unit test only asks whether the final program pa
arXiv:2610.14937v1 Announce Type: new Abstract: How do language models generalize from their training data? This is a central challenge for alignment: models reliably learn their training distribution
arXiv:2610.20288v1 Announce Type: new Abstract: Conditional generative models are increasingly used for scientific prediction beyond the direct training support. Yet scientific questions often concern
arXiv:2610.20587v1 Announce Type: cross Abstract: An agentic market is a decentralized serving-time market where AI agents bid to claim each user prompt. An agent's bid is based on its expected value
arXiv:2412.12877v3 Announce Type: replace Abstract: Recent Artificial Intelligence (AI)-based video editing has enabled users to edit videos through simple text prompts, significantly simplifying the
arXiv:2610.20538v1 Announce Type: new Abstract: Multimodal code intelligence connects the symbolic world of programs with the visual world their execution creates. Interest in this capability is burge
arXiv:2610.19762v1 Announce Type: new Abstract: Medical prescribing errors for multimorbid patients, who require complex drug regimens, are a major patient safety concern. These errors often stem from
arXiv:2610.16778v1 Announce Type: cross Abstract: Cloud graphical user interface (GUI) agents send instructions and screenshots to remote planners, exposing personally identifiable information (PII).
arXiv:2610.19336v1 Announce Type: new Abstract: Digital twins are increasingly used in robotics to simulate interactions, predict action outcomes, and support planning. However, constructing accurate
arXiv:2610.14912v1 Announce Type: new Abstract: Language models are increasingly used to create synthetic survey samples, also called silicon samples. Decision models are a new class of language model
arXiv:2610.16175v1 Announce Type: new Abstract: Real-world studies (RWS) analyze routinely collected healthcare data, such as electronic health records and insurance claims, to estimate treatment effe
arXiv:2610.14774v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly expected to orchestrate diverse tools over long-horizon tasks. Existing agents typically use Direct Tool C
arXiv:2610.19439v1 Announce Type: new Abstract: While LLM-based agent systems have demonstrated remarkable proficiency in reasoning and solving complex real-world tasks, they also come with substantia
arXiv:2610.19588v1 Announce Type: cross Abstract: We consider the problem of estimating the background intensity of a Hawkes process when the triggering mechanism is known, treating the background as
arXiv:2505.13546v2 Announce Type: replace-cross Abstract: Automatic prompt generation plays a crucial role in enabling general-purpose multi-agent systems to perform diverse tasks autonomously. Existi
arXiv:2606.13349v2 Announce Type: replace Abstract: Effective peer review requires adaptive investigation that responds to evidence emerging from each paper. Existing LLM-based reviewers largely organ
arXiv:2606.16569v2 Announce Type: replace Abstract: Registering two captures of the same indoor space taken at different times underpins persistent spatial memory for robots and AR systems, yet the re
arXiv:2610.19738v1 Announce Type: new Abstract: Large protein language models provide a powerful framework for learning sequence-function relationships and guiding experimental design. However, archit
arXiv:2610.17837v1 Announce Type: cross Abstract: Large language model (LLM) agents are increasingly used for vulnerability analysis, yet existing benchmarks provide limited coverage of exploitation t
arXiv:2610.20004v1 Announce Type: new Abstract: Transformers can perform in-context reinforcement learning without parameter updates. However, existing theoretical constructions often require context
arXiv:2606.18060v2 Announce Type: replace Abstract: As Large Language Model based agents enter autonomous scientific research, their ability to resist pseudoscience becomes increasingly important. Oth
arXiv:2610.14570v1 Announce Type: new Abstract: Large language models (LLMs) support social simulation, but faithfully reproducing real users requires grounding both structured platform decisions and
arXiv:2610.16480v1 Announce Type: new Abstract: Determining crystal structures from powder X-ray diffraction (PXRD) would enable routine characterization of newly synthesized materials, including thos
arXiv:2610.19777v1 Announce Type: new Abstract: Autoregressive models have proven effective for triangular mesh generation by transforming it into predicting the next face, converting the non-differen
arXiv:2610.18198v1 Announce Type: new Abstract: Knowledge graph link prediction involving unseen entities and relations requires learning transferable reasoning patterns from observed graph structure.
arXiv:2601.08689v3 Announce Type: replace Abstract: Large Language Models (LLMs) have shown strong capabilities in finance-oriented question answering, yet their evaluation on professional quantitativ
arXiv:2610.19912v1 Announce Type: new Abstract: Reliable validation of machine learning models is a crucial step in designing robust and trustworthy systems. Yet validation relies on annotated test se
arXiv:2610.20494v1 Announce Type: new Abstract: Pretrained representations are increasingly used to share and reuse information from medical images without exposing the original scans, but it is uncle
arXiv:2502.10570v3 Announce Type: replace-cross Abstract: Mobile gaze tracking on handheld devices commonly relies on appearance-based 2D gaze estimation from the device's front-facing RGB camera. Alt
arXiv:2610.16133v1 Announce Type: cross Abstract: Puzzles offer a natural testbed for Large Language Models (LLMs) reasoning because they pose verifiable goals under partial information and require mu
arXiv:2610.16730v1 Announce Type: new Abstract: The rapid advancement of foundation models and edge intelligence is transforming wireless networks from data-oriented communication systems into artific
arXiv:2610.19758v1 Announce Type: new Abstract: We present Lumen, The open-source model is available at, our submission to the WMT 2026 General Machine Translation Shared Task. We focus on instruction
arXiv:2610.19294v1 Announce Type: new Abstract: This work concerns our submission for the Multilingual track of the 2026 BabyLM Challenge. We improve on our baseline using data that has been summarize
arXiv:2610.19385v1 Announce Type: new Abstract: Large Language Model (LLM) unlearning is often evaluated primarily by target suppression and clean retain utility. These metrics can miss a local failur
arXiv:2610.15685v1 Announce Type: new Abstract: Conventional distillation transfers capability through teacher-generated demonstrations. LLM-as-a-Judge knowledge distillation offers a distinct and inc
arXiv:2610.18143v1 Announce Type: new Abstract: Prefix reuse improves LLM inference by sharing the KV cache of common prompt prefixes. This helps only if the scheduler can execute a matched branch in