Knowledge catalogue
arXiv:2610.17503v1 Announce Type: new Abstract: Event logs are ubiquitous across real-world domains, including business processes, manufacturing workflows, healthcare, and many other operational syste
arXiv:2610.14951v1 Announce Type: new Abstract: Feed-forward geometric foundation models (GFMs) directly predict dense geometry and camera poses from batches of images. Emerging visual SLAM methods ch
arXiv:2610.16744v1 Announce Type: new Abstract: Video large language models (Video LLMs) encode each frame into hundreds of visual tokens, making video inference expensive. Existing methods reduce thi
arXiv:2610.18023v1 Announce Type: new Abstract: Graph fraud explanation generation emerges as an important task, which requires jointly leveraging graph structure and content information to produce hu
arXiv:2610.15284v1 Announce Type: new Abstract: Drug discovery requires efficient exploration of an astronomically large chemical space. Molecular graph diffusion models offer a promising approach to
arXiv:2610.14568v1 Announce Type: new Abstract: In autoregressive video generation, retaining all historical key-value (KV) states increases memory usage and per-step attention costs as videos grow lo
arXiv:2610.17639v1 Announce Type: new Abstract: Aesthetic image cropping improves composition by balancing subjects, context, and image boundaries. Large vision-language models bring semantic knowledg
arXiv:2610.14445v1 Announce Type: new Abstract: In film production, chroma keying composites an approved foreground performance into a new environment, but conventional workflows require coordinated b
arXiv:2610.17191v1 Announce Type: new Abstract: Linear-time sequence models typically store long-context information in a recurrent state. A fixed-size state limits how much information can be stored,
arXiv:2610.17859v1 Announce Type: new Abstract: Thermal-to-visible (T2V) face translation has important applications in nighttime biometric recognition, low-light surveillance, and human interpretatio
arXiv:2610.15922v1 Announce Type: new Abstract: Autoregressive (AR) video generation enables long-horizon synthesis but requires repeated forward passes through large diffusion transformers. Training-
arXiv:2610.16569v1 Announce Type: cross Abstract: Relevance prediction between user queries and items is a fundamental component of e-commerce search systems. Traditionally, high-quality relevance lab
arXiv:2610.15390v1 Announce Type: cross Abstract: Audio Large Language Models (Audio LLMs) are embedded in agents for smart homes, vehicles, wearables, and embodied systems, where acoustic inputs can
arXiv:2602.00628v3 Announce Type: replace Abstract: We investigate the extent to which an LLM's hidden-state geometry can be recovered from its behavior in psycholinguistic experiments. Across eight i
arXiv:2610.14038v1 Announce Type: new Abstract: Embodied Artificial Intelligence (AI) introduces cyber-physical risks because digital failures and attacks can cause physical harm. This survey organize
arXiv:2511.11984v2 Announce Type: replace Abstract: Fine-grained glomerular subtyping is essential for kidney biopsy interpretation, yet it presents a harder setting than the broad organ- or disease-l
Across industries, the U.K. is putting the full stack to work — and the scale of deployment is growing fast, from enterprises transforming their businesses to startups solving some of the planet’s har
arXiv:2610.16058v1 Announce Type: new Abstract: Reliable scene understanding requires deciding which predictions to trust, retain, or inspect. In semantic segmentation, component failure predictors su
arXiv:2610.14482v1 Announce Type: new Abstract: Autonomous Aerial Vehicle (AAV) trajectory planning requires real-time and accurate safety gradient guidance, especially in dynamic environments. Existi
arXiv:2610.14067v1 Announce Type: new Abstract: Competitive humanoid table tennis requires two distinct abilities: executing a desired return and deciding where to return the ball. We separate these t
arXiv:2607.15433v2 Announce Type: replace Abstract: Quantum machine learning ideas are typically absent from traditional machine learning curricula and are instead introduced in upper-level courses on
arXiv:2610.14245v1 Announce Type: new Abstract: An LLM-directed excavator can execute mechanically feasible motion whose destination or authority no longer matches the operator's approval. We propose
arXiv:2610.17468v1 Announce Type: cross Abstract: As the complexity of space missions increases, autonomous spacecraft guidance must accommodate transitions between mission phases with distinct dynami
arXiv:2610.16868v1 Announce Type: new Abstract: Simplicity bias, which can arise from sequential feature learning during training, has been proposed as a general explanation for the success of deep le
arXiv:2601.00978v2 Announce Type: replace Abstract: Human-robot collaboration (HRC) in structured assembly requires reliable state estimation and adaptive task planning under noisy perception and huma
arXiv:2610.17630v1 Announce Type: cross Abstract: In outdoor environments, varying terrain and contact conditions can cause identical action commands to produce different motion outcomes for quadruped
arXiv:2610.18057v1 Announce Type: new Abstract: Transformers can implement reinforcement-learning algorithms in context, yet how off-policy control emerges within Transformers remains poorly understoo
arXiv:2610.14098v1 Announce Type: new Abstract: Facade articulation at building scale is usually resolved manually or through parametric systems that encode design intent as explicit rules. This paper
arXiv:2610.14622v1 Announce Type: new Abstract: Extreme rainfall can rapidly degrade road-network functionality (RNF), disrupting emergency mobility, accessibility, evacuation, logistics, and infrastr
arXiv:2610.16236v1 Announce Type: new Abstract: Morphogenesis is driven by the interplay of genetic regulation and tissue mechanics. In vivo video data is limited, particularly under genetic mutations
arXiv:2610.16364v1 Announce Type: new Abstract: Speech-driven visual grounding in remote sensing (RSVG) removes the typing bottleneck of text-based interaction and is intended to preserve prosodic int
arXiv:2610.18098v1 Announce Type: new Abstract: Deleting singular components offers a precise way to remove a capability from a language model, yet the first-order spectral saliency used to rank compo
arXiv:2610.16984v1 Announce Type: new Abstract: Offline reinforcement learning aims to learn effective policies from fixed datasets without environment interaction. Although generative models such as
arXiv:2610.17706v1 Announce Type: new Abstract: Large vision-language models often exhibit object hallucination, generating claims that are not supported by the input image. To mitigate this issue, we
arXiv:2511.22150v3 Announce Type: replace Abstract: Studying the shape of text embedding spaces enhances our understanding of model behavior and how geometry affects downstream task performance. While
arXiv:2610.14437v1 Announce Type: new Abstract: A platform that post-trains one base model for many business lines often has more lines than experts it can maintain, so lines must share experts, yet l
arXiv:2610.14561v1 Announce Type: new Abstract: Most existing approaches rely on video or motion-capture data for reinforcement learning (RL) training; however, all of these methods require an upper-l
arXiv:2610.16862v1 Announce Type: new Abstract: Optical music recognition (OMR) for medieval chant lacks training data linking manuscript images to musical symbols across notational families. Using ex
arXiv:2610.15752v1 Announce Type: new Abstract: Learned real-time supersampling accumulates jittered low-resolution samples along motion vectors. Many methods use a temporal consistency loss to reduce
arXiv:2610.14140v1 Announce Type: cross Abstract: Image-level MRI harmonization is often evaluated with a frozen site probe, a site classifier trained on raw scans and applied unchanged to harmonized
arXiv:2610.15331v1 Announce Type: new Abstract: Full-waveform inversion (FWI) is a powerful approach for reconstructing subsurface velocity models, but its practical performance is limited by ill-cond
arXiv:2610.17175v1 Announce Type: new Abstract: Decision models such as Jev score candidate answers or actions. A small decision head trained label-free can recover about 99% of a frozen language mode
arXiv:2610.14917v1 Announce Type: new Abstract: Robust motion planning and control for manipulators is the problem of guaranteeing safe execution and collision-free motion under disturbances. The Kino
arXiv:2610.16558v1 Announce Type: cross Abstract: World models capture environment dynamics and support counterfactual reasoning for planning. In image-goal navigation, where the target often lies bey
arXiv:2610.15398v1 Announce Type: new Abstract: Large language models (LLMs) demonstrate strong generalization across a broad range of reasoning and generation tasks, but their large parameter counts
arXiv:2610.18779v1 Announce Type: new Abstract: Video diffusion models generate visually compelling short-term sequences but often struggle to preserve scene geometry and object structure over time. I
This continues the small-model browser experiments from the previous posts. Two standard, off-the-shelf models ran locally on the same Samsung Galaxy S21: Gemma 4 E2B, Q3_K_M as the reasoner Qwen3.5-0
arXiv:2610.15183v1 Announce Type: new Abstract: The rapid proliferation of distributed energy resources (DERs) aggregated by virtual power plants (VPPs) elevates cybersecurity risk by expanding the at
arXiv:2610.18834v1 Announce Type: new Abstract: Visual reasoning is an important capability for vision-language models (VLMs) to understand visual evidence, spatial structure, constraints, and state c
arXiv:2610.13995v1 Announce Type: new Abstract: Post-training large language models (LLMs) on two-player zero-sum games provides a verifiable reward, and the gains have been shown to transfer to gener
Gary Marcus will be speaking at the @Bloomberg New Economy Forum in New Delhi tomorrow, October 15, on AI reliability, control and safety. @GaryMarcus Hope you’ll connect all the dots between… LLM bul
arXiv:2610.17760v1 Announce Type: new Abstract: Gaussian process bandits exploit similarities among configurations to optimize prompts, retrieval systems, and agent workflows. In these applications, h
arXiv:2610.17513v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) allows for high-quality real-time novel-view synthesis. Since its inception in 2023, its explicit and highly configurable s
Gemini 4 Argon, Muse Spark 1.3, and Muse Wonder 1.0 are all really good at pdf parsing. Come check it out on OpenDocRouter! https://www.opendocrouter.ai/ Media OpenDocRouter makes it dead-simple to st
Gemini 4 TikZ unicorn From GPT-4 to GPT-6. Sparks was a remarkably prescient paper that got a lot of pushback at the time, but absolutely sensed where the vibes were heading with LLMs based on a lot o
arXiv:2610.15900v1 Announce Type: new Abstract: We present Gen Through the Lens, a camera-controllable image-to-video generation framework that synthesizes videos from a given reference image while en
arXiv:2610.15707v1 Announce Type: new Abstract: A central desideratum in model editing is generalization to complex tasks, which prior work formalizes under a direct generalization paradigm: treating
arXiv:2610.14008v1 Announce Type: new Abstract: This study investigates generalized boundary representations and transfer learning for physics-informed neural-network (PINN) estimation of spatially va
This post walks you through building an AI agent system with Amazon Bedrock AgentCore that automates PowerPoint presentation creation from enterprise documents. A supervisor agent, Retrieval Augmented
Generative AI: a yet-to-be-profitable industry facing price wars, increased competition, increased liability and safety concerns, and declining customer confidence, while often failing to deliver demo