Knowledge catalogue
arXiv:2609.20178v1 Announce Type: new Abstract: Accurately predicting pedestrian intentions is crucial for ensuring safe and proactive interaction between autonomous vehicles and pedestrians. However,
arXiv:2609.20152v1 Announce Type: new Abstract: Generally, most voice agents are cascaded systems, i.e., an ASR model transcribes the caller's audio, a language model reads the transcript and decides
arXiv:2607.14962v2 Announce Type: replace-cross Abstract: Text-to-image (T2I) models can synthesize realistic, prompt-aligned images, yet samples generated for the same prompt often cover only a small
arXiv:2609.20650v1 Announce Type: new Abstract: Federated learning enables collaborative training without sharing patient-level data, but most studies remain simulations. Based on five requirements de
arXiv:2609.20124v1 Announce Type: cross Abstract: Evaluating live streaming speech synthesis (TTS) requires assessing fine-grained, highly expressive prosody such as emotion, intonation, and energy wh
I had Astra run a multi-hour investigation into speeding up local MoE inference while keeping the model weights and quantization unchanged. The experiments covered Qwen3.6-35B-A3B and Qwen3.8 Flash-Ne
arXiv:2609.20195v1 Announce Type: cross Abstract: Audio-language models increasingly generate confident music descriptions that are unsupported by the input audio. We present, to our knowledge, the fi
Been working on this backend migration for like two weeks and my chat with ChatGPT is one of those endless scrolls. Last Tuesday it confidently told me we'd 'decided' on the wrong database. We had lit
arXiv:2609.20388v1 Announce Type: cross Abstract: Vision-Language Navigation in Continuous Environments (VLN-CE) requires an embodied agent to execute long-horizon instructions in unknown environments
arXiv:2609.19541v1 Announce Type: new Abstract: Conventional robot planning methods seek collision-free paths to a goal but fail when all paths are blocked. In these cases, the robot must determine wh
arXiv:2609.20327v1 Announce Type: cross Abstract: We study smooth strongly convex--strongly concave minimax optimization with general nonlinear coupling in the deterministic unconstrained setting. We
arXiv:2609.20160v1 Announce Type: new Abstract: Monitoring flying animals is important for understanding and protecting biodiversity, but nocturnal species such as bats are difficult to observe in the
arXiv:2609.19154v1 Announce Type: new Abstract: While Large Language Models (LLMs) achieve high accuracy on established Classical Chinese Poetry benchmarks, it remains challenging to distinguish trans
arXiv:2609.19961v1 Announce Type: new Abstract: Networked low-altitude unmanned aerial vehicles (UAVs) need reliable and adaptive decision-making capabilities to operate under uncertain observations,
arXiv:2609.20323v1 Announce Type: new Abstract: Three-dimensional reconstruction from unorganized point clouds remains a challenging problem in computer vision, geometric modeling, and computer-aided
arXiv:2609.19529v1 Announce Type: cross Abstract: Suppose we observe the first n points of a sequence of random variables having length n+1, and wish to estimate a functional of the unobserved final p
Saw this little dude in a Forbes article (https://www.forbes.com/sites/johnkoetsier/2026/08/18/american-humanoid-robot-launches-for-just-1688-delivery-this-fall-made-in-san-francisco/) This is definit
arXiv:2609.20523v1 Announce Type: cross Abstract: Quantum communication underpins secure information processing and scalable quantum networks. In particular, remote state preparation (RSP) enables eff
arXiv:2609.19947v1 Announce Type: new Abstract: LLM-based AI agents process user requests through iterative reasoning and tool execution, often involving the invocation of remote LLM APIs with local t
arXiv:2609.20299v1 Announce Type: new Abstract: Information aggregation across model layers are revealed to improve OOD detection. In contrast to crafting a method for layer-wise information aggregati
arXiv:2609.19210v1 Announce Type: cross Abstract: Graph neural networks are widely used for transductive node classification, with accuracy typically measured on randomly drawn train/validation/test s
Being a computer scientist who refuses to find anything about LLMs interesting right now is a bit like being a geneticist who refuses to find anything interesting about the recently opened Jurassic Pa
arXiv:2609.20578v1 Announce Type: cross Abstract: Connected-vehicle safety evaluations rely on coupled traffic and network simulations, but standard channel models ignore radio resource competition in
arXiv:2609.19511v1 Announce Type: cross Abstract: Feature importance is central to interpretable machine learning, but the term 'importance' encompasses several fundamentally different notions of rele
arXiv:2609.19768v1 Announce Type: new Abstract: Multivariate ocean forecasting must exploit shared evolution in a coupled ocean system while adapting to the heterogeneous statistical and dynamical cha
arXiv:2609.19709v1 Announce Type: new Abstract: Batched multi-armed bandits update on a service's own schedule, and the usual implementation carries each arm's absolute reward rate from one update to
arXiv:2609.19302v1 Announce Type: new Abstract: Open datasets describing human behavior in environments shared with mobile robots remain limited, particularly for retail activities that combine locomo
Hi everyone, I’ve been experimenting with local LLMs on my 48 GB RAM MacBook Pro and I’m still trying to figure out what the best setup is. Ollama feels very fast, which I really like. The problem for
arXiv:2609.19582v1 Announce Type: new Abstract: Assembly, wear, and component replacement perturb the sensor extrinsics and joint zeros encoded by a humanoid CAD model. Existing procedures calibrate o
arXiv:2609.20566v1 Announce Type: cross Abstract: Animal demonstrations provide quadruped robots with natural and distinctive gait styles that are difficult to specify through hand-crafted rewards. Ho
arXiv:2609.20734v1 Announce Type: new Abstract: Reasoning and agentic workloads increasingly demand efficient long-context inference. Yet full-attention decoding reads the growing history at every ste
arXiv:2602.01928v3 Announce Type: replace-cross Abstract: Privacy preservation is critical in many high-stakes domains such as medicine and finance, where sensitive data must be analyzed without compr
arXiv:2609.19955v1 Announce Type: new Abstract: We study the problem of recovering the parameters of a multivariate Ornstein-Uhlenbeck (OU) process from steady-state observational and interventional d
arXiv:2603.21785v2 Announce Type: replace Abstract: Visual odometry (VO) frontends are typically tuned offline by domain experts on pre-recorded datasets and then deployed with fixed hyperparameters.
arXiv:2609.19891v1 Announce Type: new Abstract: Gaussian Processes (GPs) are widely used as surrogates for black-box functions in sequential decision-making problems such as Bayesian optimization (BO)
arXiv:2609.20454v1 Announce Type: cross Abstract: Accurate optimization of a supervised spectral objective need not produce an accurate population subspace or a better predictive representation. We in
Oops Anthropic IPO moved back to November. (Maybe second delay? And OpenAI IPO moved back to 2027. Making those S-1’s look good given the circumstances is hard work. *ANTHROPIC PLANS TO STAGE ITS IPO
arXiv:2609.19230v1 Announce Type: new Abstract: Ultrasound is the most widely deployed imaging modality worldwide, yet clinical AI remains fragmented into narrow single-task models that fail when devi
arXiv:2609.19358v1 Announce Type: new Abstract: Three-dimensional object detection for autonomous driving is dominated by detectors trained on large corpora of human-annotated 3D boxes. Such a detecto
arXiv:2609.19695v1 Announce Type: new Abstract: Federated learning (FL) enables privacy-preserving, on-device training across heterogeneous Internet-of-Things (IoT) deployments such as smart-city wate
arXiv:2609.20756v1 Announce Type: cross Abstract: As scaling pre-training data alone yields diminishing returns, post-training is becoming increasingly important across physical AI domains such as aut
arXiv:2609.19176v1 Announce Type: cross Abstract: Multi-organ segmentation is often challenged by partially annotated datasets and domain shifts across different imaging sources. To address these limi
arXiv:2505.06756v2 Announce Type: replace-cross Abstract: The problem of using proximity (similarity or dissimilarity) data for the purpose of 'adding a point to a vector diagram' was first studied by
arXiv:2609.20658v1 Announce Type: new Abstract: When does work done with AI still feel like ours? As AI becomes woven into everyday tasks, we must examine what happens to our sense of ownership and co
arXiv:2609.20634v1 Announce Type: new Abstract: Allen's interval algebra is a qualitative calculus for temporal relations, but its thirteen base relations are crisp predicates over exact interval boun
arXiv:2609.19853v1 Announce Type: cross Abstract: Between a screenplay and a film sits a planning problem that is spatial first: who stands where, and what a camera sees from where it stands. An image
arXiv:2609.20177v1 Announce Type: new Abstract: Forecasting corporate tax avoidance proxies from firm--year panel data is challenging because predictive signals are distributed across short firm histo
arXiv:2609.20816v1 Announce Type: cross Abstract: Professional design requires any-color control: the ability to specify an object's target color with any 24-bit hex value for image generation and edi
arXiv:2609.19226v1 Announce Type: cross Abstract: AI-mediated platforms coordinate work through LLM agents acting for different principals. In these workflows, privacy loss can be created before a fin
arXiv:2609.20539v1 Announce Type: new Abstract: A popular selling point of diffusion large language models (dLLMs) is their capacity for parallelism: the ability to generate sequences of text far more
arXiv:2609.19872v1 Announce Type: new Abstract: 3D assembly is fundamental to modern manufacturing and digital content creation. In this paper, we present PART, a unified transformer-based framework f
arXiv:2609.19463v1 Announce Type: new Abstract: We present ParticleSplat, a self-supervised object-centric learning method that decomposes scenes into a set of latent ''particles'' representing semant
arXiv:2609.19985v1 Announce Type: cross Abstract: Fine-tuning foundation models on new tasks inevitably suffer from catastrophic forgetting. While existing works attempt to mitigate this on the basis
'People built the test, removed restraints, defined the objective, left a route open and decided not to stop what was happening. Calling the result 'rogue AI' does more than sensationalize it. It allo
arXiv:2609.20110v1 Announce Type: new Abstract: Straight-through processing (STP) on extracted key-value fields from financial documents without human review requires a calibrated probability together
arXiv:2609.19215v1 Announce Type: cross Abstract: Traditional codecs treat every region of a frame alike; a generative layer can instead degrade the regions a viewer attends to least and reconstruct t
arXiv:2311.08493v2 Announce Type: replace-cross Abstract: This research aims to investigate the classification accuracy of various state-of-the-art image classification models across different categor
arXiv:2609.19542v1 Announce Type: new Abstract: Open-vocabulary segmentation enables rich semantic perception for UAVs, but frame-wise predictions can remain temporally inconsistent across repeated ob
arXiv:2605.13481v2 Announce Type: replace Abstract: We introduce PersonalAI 2.0 (PAI-2), a novel framework designed to enhance LLM-based systems through integration of external knowledge graphs (KGs).
arXiv:2609.20296v1 Announce Type: new Abstract: A myoelectric interface needs calibration from the user before it will function. Earlier work has treated calibration as a quantity, but has not asked t