Knowledge catalogue
arXiv:2610.10407v1 Announce Type: cross Abstract: As option markets grow and AI advances, agentic systems for option trading are gaining increasing attention. Language-model-based agents can reason ov
arXiv:2610.09418v1 Announce Type: new Abstract: Pointing-gesture visual grounding requires connecting hand geometry with the visual identity and extent of a referred object. A central challenge for co
arXiv:2610.09025v1 Announce Type: new Abstract: Indexer-based sparse attention reduces the cost of core attention by passing only a fixed, small number of important tokens to it. However, the indexer
arXiv:2610.09116v1 Announce Type: new Abstract: The rapid growth of 3D Gaussian Splatting (3DGS) research demands significant effort to reimplement papers before building on them. We introduce SPLATIF
arXiv:2610.10415v1 Announce Type: cross Abstract: Pretrained text-to-speech (TTS) models can generate expressive speech, but reliable inference-time emotion control remains challenging: prompts and re
arXiv:2610.09598v1 Announce Type: new Abstract: Uterine contractions in fetal MRI are typically identified manually and discarded, limiting insights into contraction dynamics. We formalize Uterine Con
arXiv:2610.08848v1 Announce Type: cross Abstract: Glioblastoma (GBM), an aggressive primary brain tumor, is routinely monitored with longitudinal MRI after treatment. Distinguishing stable disease (SD
arXiv:2610.09566v1 Announce Type: new Abstract: Imitation learning policies that integrate multiple sensory modalities are prone to overreliance on a dominant modality, such as vision, during training
arXiv:2610.08975v1 Announce Type: new Abstract: A plethora of new adaptive optimizers are designed to efficiently estimate and use minibatch gradient statistics to shape parameter updates, but they ar
arXiv:2610.09371v1 Announce Type: cross Abstract: Calibrated uncertainty quantification is essential to ensuring AI agents are trustworthy and reliable. However, when agents seek to maximize user enga
arXiv:2610.09255v1 Announce Type: new Abstract: Neural PDE surrogates are trained on numerical solver outputs that contain both physical evolution and solver-specific discretization errors. Because su
arXiv:2610.09441v1 Announce Type: new Abstract: Microsatellite instability-high (MSI-H) and high tumor mutational burden (TMB-H) are clinically relevant biomarkers, yet their histopathological predict
arXiv:2610.09408v1 Announce Type: new Abstract: Audio-visual multi-segment grounding (AV-MSG) in untrimmed videos, reasoning over audio-visual evidence and predicting multiple segments for a query, is
arXiv:2610.09462v1 Announce Type: new Abstract: Backdoored vision-language-action (VLA) policies can preserve benign task performance while producing malicious actions when a trigger appears. Detectin
arXiv:2610.10076v1 Announce Type: cross Abstract: Calibration is an essential requirement for probabilistic predictions to be useful for decision making. While state-of-the-art prediction methods ofte
arXiv:2610.09637v1 Announce Type: cross Abstract: How can we verify whose music contributed to an AI-generated output? This paper demonstrates how input-based attribution can provide verifiable eviden
arXiv:2610.10124v1 Announce Type: cross Abstract: Generative recommenders return a limited candidate set and may omit observed targets before reranking. A training strategy appends these missed target
arXiv:2610.08810v1 Announce Type: new Abstract: Fine-tuned geospatial foundation models (GeoFMs) pretrained on large satellite archives have been shown to improve crop classification accuracy and geog
arXiv:2603.15614v2 Announce Type: replace Abstract: Recent video diffusion models achieve strong visual quality and temporal coherence, but still lack coordinated control over scene layout, customized
arXiv:2610.09281v1 Announce Type: new Abstract: In Bayesian inverse problems, posterior sampling requires generating samples that are consistent with given observations while capturing the range of pl
arXiv:2610.09087v1 Announce Type: new Abstract: Large language models are informing decisions with ever-higher stakes. As the consequences of their errors grow, a central question becomes harder to ig
arXiv:2610.09703v1 Announce Type: cross Abstract: Token-Pruning accelerates Vision-Language Models by removing redundant visual tokens, yet its safety implications remain underexplored. In this work,
arXiv:2610.09559v1 Announce Type: new Abstract: Wi-Fi sensing promises to turn the everyday wireless signals that already surround us into ubiquitous sensors for human sensing. However, a fundamental
arXiv:2602.22647v3 Announce Type: replace-cross Abstract: Generative retrieval has emerged as a powerful paradigm for LLM-based recommendation. However, industrial recommender systems often benefit fr
arXiv:2610.10270v1 Announce Type: new Abstract: World action models (WAMs) have emerged as an important class of generalist robot policies, aiming to transfer video prediction priors to action learnin
arXiv:2610.10197v1 Announce Type: new Abstract: Accurate contact modeling is fundamental to understanding hand-object interaction, yet existing contact representations are typically restricted to obje
arXiv:2610.09647v1 Announce Type: cross Abstract: Post-training adapts language models in non-stationary environments. Practitioners monitor representation health with RankMe and related spectral stat
arXiv:2610.10335v1 Announce Type: new Abstract: Visual in-context learning (ICL), well suited to label-scarce medical imaging, uses support image-label pairs to demonstrate input-output mappings, whil
arXiv:2610.10118v1 Announce Type: cross Abstract: Long-horizon reasoning demands access to earlier information at a manageable generation cost. Full-history attention incurs growing storage and comput
arXiv:2610.09718v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models acquire broad manipulation capabilities via large-scale pretraining, yet eliciting them through language requires
arXiv:2610.08983v1 Announce Type: new Abstract: Generative inpainting of brain MRI volumes is essential for synthesizing healthy tissue in pathological regions, improving the accuracy and reliability
I've been tinkering with GLM-5.3-Flash on two 64GB CMP 170HX cards for a while, and the setup is finally stable enough that I figured I'd share it. I also compared it against the Qwen3.8-Flash-Next se
arXiv:2610.08469v1 Announce Type: new Abstract: Endovascular catheter navigation relies on continuous fluoroscopy, exposing patients and clinical staff to ionizing radiation throughout the procedure.
arXiv:2610.06980v1 Announce Type: new Abstract: Sensing technologies have advanced rapidly across industries ranging from energy to automotive manufacturing. These systems generate high-dimensional (H
arXiv:2610.07857v1 Announce Type: new Abstract: This study formulates individual route reproduction as a shortest-path problem over learned driver-specific latent link costs. The central idea is that,
arXiv:2610.07339v1 Announce Type: cross Abstract: Tactical Combat Casualty Care (TC3) requires responders to connect visual observations of injuries and interventions with established clinical guidanc
arXiv:2610.08365v1 Announce Type: new Abstract: We adapt Stevens's power law to measure the innate ability of AI models to read visualizations, which can reveal the built-in perceptual mechanisms of a
arXiv:2610.07544v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to judge how well an advertisement matches a query, but the fairness of these judgments has received
arXiv:2610.07426v1 Announce Type: new Abstract: Accent classifiers are typically trained with a fixed label inventory and cannot accommodate new accent categories as new data becomes available. Moreov
arXiv:2610.08444v1 Announce Type: new Abstract: Vision-language-action (VLA) policies repeatedly invoke inference to control robots, making graphics processing unit (GPU) energy a recurring cost of ta
arXiv:2610.06949v1 Announce Type: cross Abstract: Large audio language models answer questions about speech, sound, and music, yet their accuracy drops sharply on tasks that need fine-grained acoustic
arXiv:2603.01295v2 Announce Type: replace-cross Abstract: Joint lesion segmentation and tissue classification in breast ultrasound are usually trained with a shared encoder, so the two branches stop e
arXiv:2604.02691v2 Announce Type: replace Abstract: Deep learning based semantic communication has achieved significant progress in wireless image transmission, but most existing schemes rely on fixed
arXiv:2508.19073v4 Announce Type: replace-cross Abstract: Deep learning training commonly runs on shared multi-tenant GPU servers, where exclusive allocation provides isolation but can leave resources
arXiv:2610.06971v1 Announce Type: new Abstract: Traditional data pipelines are notoriously brittle, often failing due to upstream schema drift, API contract changes, or website DOM modifications. Pres
arXiv:2610.08775v1 Announce Type: new Abstract: Large language models (LLMs) can solve many narrow tasks, but querying them separately for millions of related instances can be prohibitively expensive.
arXiv:2610.07707v1 Announce Type: new Abstract: Conversational AI assistants with long-term memory extract facts from user messages into a store consulted in later conversations. A stated plan can ent
arXiv:2610.07128v1 Announce Type: cross Abstract: Aggregating the preferences of diverse user groups into a collective outcome raises fundamental challenges of equity, diversity, and inclusion (EDI):
arXiv:2610.01108v2 Announce Type: replace Abstract: Retrieval-based speculative decoding (SD) drafts tokens by copying continuations from existing text, which suits coding agents that repeatedly repro
arXiv:2610.07566v1 Announce Type: new Abstract: Feed-forward novel view synthesis methods achieve strong generalization from posed multi-view inputs, but scaling them to large input view sets remains
arXiv:2610.07271v1 Announce Type: new Abstract: Linkage algorithms for hierarchical clustering (HC) are a powerful and efficient framework for constructing clustering trees, yet it is often unclear wh
arXiv:2610.08164v1 Announce Type: cross Abstract: Low-rank quantization error compensation (LQEC) recovers the accuracy lost under aggressive weight quantization by attaching a closed-form rank-r adap
arXiv:2610.07457v1 Announce Type: cross Abstract: Fine-grained mixed-precision quantization promises efficient large language model inference, but local precision choices can conflict with regular GPU
arXiv:2610.08037v1 Announce Type: new Abstract: Language models frequently generate outputs in unintended languages or scripts, a phenomenon known as off-target generation. While existing research has
arXiv:2610.07438v1 Announce Type: cross Abstract: Artifact removal routinely precedes the classification of electrodermal activity (EDA), on the assumption that a cleaner signal supports a better deci
arXiv:2610.07637v1 Announce Type: cross Abstract: Many real-world datasets exhibit unusually large values far more frequently than predicted by Gaussian models. Heavy-tailed distributions capture this
arXiv:2610.08400v1 Announce Type: cross Abstract: Large-scale self-supervised pretraining has reshaped modern machine learning, substantially advancing the ability of language and vision models to gen
arXiv:2610.08119v1 Announce Type: new Abstract: World-action models (WAMs) such as Cosmos 3 jointly generate future video and robot actions from an observation and instruction. Adapting one such model
AWS DevOps Agent can diagnose production incidents but is kept in observe-and-report mode so it does not change resources directly. This post shows how to use AWS Lambda Durable Functions, Amazon Even
arXiv:2610.06892v1 Announce Type: cross Abstract: Learning from human preference data is the dominant route to aligning language models with human values. In linear social choice, where rewards are li