Knowledge catalogue
arXiv:2503.16855v3 Announce Type: replace Abstract: Hand gesture-based Sign Language Recognition (SLR) serves as a crucial communication bridge between deaf and non-deaf individuals. While Graph Convo
arXiv:2511.08873v3 Announce Type: replace Abstract: Large language models (LLMs) are shifting from answer providers to intelligent tutors in educational settings, yet current supervised fine-tuning me
arXiv:2508.21424v3 Announce Type: replace Abstract: Deep learning models have achieved state-of-the-art performance in many computer vision tasks. However, in real-world scenarios, novel classes that
arXiv:2608.24422v1 Announce Type: new Abstract: Recovering the full 3D spine anatomy from intraoperative ultrasound is an ill-posed inverse problem, as the complete structure must be inferred from inc
arXiv:2608.23182v1 Announce Type: cross Abstract: We present a comparative study of label-free metrics for assessing the quality of representations in deep neural networks to understand their reliabil
arXiv:2603.27530v2 Announce Type: replace Abstract: Bock's 1971 algorithm is an exact primal--dual method for the minimum-cost arborescence problem, but its Algol presentation obscures the interaction
arXiv:2608.23400v1 Announce Type: cross Abstract: Discrete Diffusion Models (DDMs) have recently been introduced to recommendation systems, modeling user history as a token generation process via iter
arXiv:2505.21430v3 Announce Type: replace Abstract: Attribute-efficient PAC learning of sparse halfspaces has been a fundamental problem in machine learning theory. In recent years, machine learning a
arXiv:2608.22760v1 Announce Type: new Abstract: Byte-space Action Recognition (BAR) aims to recognize human actions directly from compressed image bitstreams without any pixel decoding. By operating e
arXiv:2608.22646v1 Announce Type: new Abstract: Diffusion language models can generate many tokens in parallel, but they still require repeated denoising steps during inference. This makes generation
arXiv:2511.22281v2 Announce Type: replace Abstract: Observing certain patches in an image reduces the uncertainty of others. Their realization lowers the distribution entropy of each remaining patch f
arXiv:2608.22033v1 Announce Type: new Abstract: Stable quadrupedal locomotion on sparse terrain requires selecting state-relevant terrain evidence for precise foot placement. Model-based foothold plan
arXiv:2602.16469v2 Announce Type: replace Abstract: Machine-translated data is widely used in multilingual NLP, particularly where native text is scarce. However, translated text differs systematicall
arXiv:2608.23189v1 Announce Type: new Abstract: We present EchoWM, an omnimodal world model for enterable generative media that responds to continuous navigation while jointly generating 720p video, e
arXiv:2608.22449v1 Announce Type: cross Abstract: Forecasting dexterous hand motions from egocentric observations is fundamental to intelligent interactive systems. Existing VLM-based methods typicall
arXiv:2508.02609v3 Announce Type: replace-cross Abstract: Graph Neural Networks (GNN) have been extensively applied to industry recommendation systems, as seen in models like GraphSageite{GraphSage},
Every extraction API demos well on a clean invoice. But what about the scanned form, the nested table, the 40-page financial report with merged headers? We tested 14 frontier systems to find out. Extr
arXiv:2608.23271v1 Announce Type: cross Abstract: As generative AI tools find increasing use in research workflows, ongoing debates on their impact, appropriateness and responsible use have led policy
arXiv:2608.22224v1 Announce Type: cross Abstract: Temporal Domain Generalization (TDG) aims to learn from historical domains and generalize to unseen future distributions under concept drift. Neverthe
arXiv:2608.21897v1 Announce Type: new Abstract: Reliable planning requires converting natural-language instructions into executable symbolic specifications, yet large language models remain brittle wi
arXiv:2608.22513v1 Announce Type: new Abstract: Neural networks can learn algebraic operations from finite examples, but it remains unclear whether this ability transfers across mathematically equival
arXiv:2608.22462v1 Announce Type: cross Abstract: Artificial neural networks can acquire new capabilities but often damage existing ones when they continue to learn. This stability-plasticity problem
arXiv:2608.21605v1 Announce Type: new Abstract: Logic Tensor Network-Enhanced Generative Adversarial Networks (LTN-GANs) inject background knowledge by grounding each logical axiom as a predicate and
arXiv:2607.02486v2 Announce Type: replace Abstract: Descriptor-free visual localization eliminates high-dimensional descriptor storage, preserves scene privacy, and simplifies map maintenance, yet its
Hi @GaryMarcus, I'm the Research Lead for this model. It's even more consequential than just Anthropic's IPO: This paper is a blueprint for how to *actually* build AI Sovereignty. https://tinyurl.com/
Mariko Wakabayashi is a Principal Applied Scientist at Microsoft who leads the development of agentic AI workflows for cybersecurity operations. She specializes in evaluating LLM‑powered systems and a
arXiv:2608.22212v1 Announce Type: cross Abstract: Causal discovery aims to understand the relationships between individual random variables. In many applications, such as brain imaging and climate mod
arXiv:2412.00776v5 Announce Type: replace Abstract: Continual learning (CL) learns from a non-stationary data stream without storing or re-training on all seen samples. Meta-continual learning (MCL) c
arXiv:2509.04226v2 Announce Type: replace Abstract: State space models (SSMs) are an emerging paradigm that achieves linear-time scaling, however, they intrinsically suffer from 'curse of memory'. The
arXiv:2608.22993v1 Announce Type: new Abstract: Students increasingly use LLMs as tutors for coursework and problem solving. Little is known about the level of assistance LLMs provide when students us
arXiv:2608.22764v1 Announce Type: new Abstract: Joint-embedding predictive architectures (JEPAs) learn latent dynamics for planning and avoid representation collapse by matching features to maximum-en
arXiv:2608.21656v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has emerged as a powerful paradigm for combining large language models (LLMs) with external knowledge sources. Howe
arXiv:2608.22273v1 Announce Type: cross Abstract: Pathological and more broadly non-canonical speech present significant challenges for automatic phoneme recognition due to systematic deviations from
arXiv:2502.15873v5 Announce Type: replace Abstract: Policymakers increasingly use development cost and compute as proxies for AI capabilities and risks. Recent laws have introduced regulatory requirem
arXiv:2608.23258v1 Announce Type: new Abstract: We propose HetSkills, a novel framework designed to progressively learn heterogeneous skills within a unified latent space for physics-based character c
arXiv:2608.22740v1 Announce Type: new Abstract: Generalizable 3D Gaussian Splatting (G-3DGS) has emerged as a promising approach for novel view synthesis undersparse-view settings. However, existing f
arXiv:2606.12849v2 Announce Type: replace-cross Abstract: Semantic mapping is a core service that enables grounded interactions in emerging Extended Reality (XR) applications such as AI assistants. De
Skild AI: Skild AI unveils S1, a robotics foundation model that it says can learn tasks never seen during pretraining, using a single video demo, without fine-tuning — UNSEEN TASKS10-MINUTE HORIZONSON
arXiv:2608.22223v1 Announce Type: cross Abstract: Anti-amyloid therapies and blood-based biomarkers are changing Alzheimer disease workups into a two-stage measurement workflow: screen broadly with ch
arXiv:2608.22772v1 Announce Type: new Abstract: Text-to-SQL aims to translate natural language questions into executable SQL queries over relational databases, requiring multi-stage structured reasoni
arXiv:2608.22622v1 Announce Type: cross Abstract: Clinical decision-making relies on identifying relevant patient information to guide diagnosis and treatment, a challenge that is especially difficult
This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. How to encourage smarter AI use in the classroom Chatbots took
arXiv:2608.21761v1 Announce Type: new Abstract: Large collections of street-view imagery provide rich visual information about urban environments, but extracting fine-grained geographic information fr
arXiv:2608.22174v1 Announce Type: new Abstract: Unified multimodal models (UMMs) can perform both understanding and generation, raising a central question: can visual generation improve understanding?
arXiv:2602.13106v2 Announce Type: replace-cross Abstract: In recent years, there has been growing interest in understanding neural architectures' ability to learn to execute discrete algorithms, a lin
arXiv:2412.06167v2 Announce Type: replace Abstract: In digital advertising, demand-side platforms (DSPs) allow advertisers to create multiple ad creatives from a single photo for real-time bidding. Wh
arXiv:2608.21234v1 Announce Type: cross Abstract: These lecture notes form the first part of a master's-level course on advanced numerical linear algebra. Their aim is not only to present the classica
arXiv:2608.20686v1 Announce Type: new Abstract: Many scientific discovery problems require searching combinatorial hypothesis spaces under complex domain constraints. Reinforcement learning (RL) offer
arXiv:2608.20382v1 Announce Type: new Abstract: We introduce a new architecture design for multimodal large language models (MLLMs), Libra, capable of both multimodal understanding and generation. Lib
Learn how to build a customizable, smart-caching knowledge management system on AWS that captures and delivers institutional (tribal) knowledge through a voice-first AI avatar. The accelerator uses Am
arXiv:2608.21286v1 Announce Type: new Abstract: Conditional Flow Matching trains generative models by regressing a network onto the velocity of a prescribed noise-to-data interpolation path. The inter
arXiv:2405.07359v2 Announce Type: replace Abstract: Accurate prediction of electricity day-ahead prices is essential in competitive electricity markets. Although stationary electricity-price forecasti
This article is from Making AI Work, MIT Technology Review’s limited-run newsletter examining how to apply LLMs across industries. To receive it in your inbox, sign up here. Chatbots took many schools
People have been talking to each other for at least 100,000 years, as best we can tell. And in all that time, there has been only one thing in the world that could learn a human language to perfect fl
arXiv:2608.20932v1 Announce Type: new Abstract: Layout-to-image generation enables explicit spatial control through bounding-box layouts, yet bounding boxes specify only instance locations and cannot
“flailing” is the word that comes to mind. either that or “dreaming” OpenAI does not want to become the application layer of AI; it wants to be the platform that other application companies build on.
Frontier labs went from 'AGI will automate the economy next year' to 'well, society just adapts slowly.' The market isn't dragging its feet because people fear change. Adoption is capped because raw L
Raffaele Huang / Wall Street Journal: The careers of Z.ai's Tang Jie and Moonshot AI's Yang Zhilin, once teacher and pupil at Tsinghua University, show that China's AI leap is no sudden development —
arXiv:2606.12428v2 Announce Type: replace-cross Abstract: In this work, we locate and analyze existing undergraduate Artificial Intelligence (AI) programs in the United States in Spring 2026, creating
At 1400x cheaper, I know I'm sticking to embeddings (dense, sparse, multi-vector), plus hybrid (incl. bm25) and rerankers. Perhaps I'd even use listwise cross-encoders, they seem interesting. can LLMs