Knowledge catalogue
arXiv:2510.23156v2 Announce Type: replace-cross Abstract: The growing demand for smart home interfaces has increased interest in non-intrusive sensing methods like vibration-based gesture recognition.
arXiv:2604.19510v1 Announce Type: new Abstract: Variability in illumination is a primary factor limiting deep learning robustness for field-based plant disease detection. This study evaluates Histogra
Every system that was regulated, either explicitly or implicitly, by the fact that they were effortful for humans (letters of recommendation, lawsuits, government filings, essays) will break. 🚨New pre
Excited to share our work on production-ready W4A8 inference, now integrated in vLLM! By combining 4-bit weights (low memory) with 8-bit activations (high compute), we hit the sweet spot for both deco
arXiv:2604.19678v1 Announce Type: new Abstract: Function vectors (FVs) are vector representations of tasks extracted from model activations during in-context learning. While prior work has shown that
arXiv:2604.19021v1 Announce Type: new Abstract: Linear attention mechanisms have emerged as promising alternatives to softmax attention, offering linear-time complexity during inference. Recent advanc
arXiv:2604.18882v1 Announce Type: new Abstract: We present a formally verified framework for patent analysis as a hybrid AI + Lean 4 pipeline. The DAG-coverage core (Algorithm 1b) is fully machine-ver
arXiv:2604.19663v1 Announce Type: cross Abstract: Counterfactual explanations (CEs) provide an intuitive way to understand recommender systems by identifying minimal modifications to user-item interac
GPT-ImageGen-2 did this in one shot, with just the prompt 'turn all of Tennyson's Ulysses into a comic, across as many pages as needed. make it great, include the full text' 10 pages, though it did us
arXiv:2512.00716v2 Announce Type: replace-cross Abstract: Covariate distribution shift occurs when certain structural features present in the test set are absent from the training set. It is a common
arXiv:2604.18753v1 Announce Type: cross Abstract: An active challenge in developing multimodal machine learning (ML) models for healthcare is handling missing modalities during training and deployment
As AI inference demand surges and enterprise compute budgets buckle under expanding workloads, x86 efficiency has emerged as one of the most powerful — and underutilized — levers in cloud financial ma
arXiv:2604.18862v1 Announce Type: cross Abstract: Bug reports, encompassing a wide range of bug types, are crucial for maintaining software quality. However, the increasing complexity and volume of bu
arXiv:2507.03828v4 Announce Type: replace Abstract: Large language models (LLMs) achieve strong performance across diverse domains but remain difficult to deploy in resource-constrained environments d
arXiv:2511.17578v2 Announce Type: replace Abstract: Existing curved-layer-based process planning methods for multi-axis manufacturing address collisions only indirectly and generate toolpaths in a pos
arXiv:2604.19673v1 Announce Type: new Abstract: Training embodied agents to understand 3D scenes as humans do requires large-scale data of people meaningfully interacting with diverse environments, ye
arXiv:2505.16662v4 Announce Type: replace Abstract: This paper presents a new method for jointly calibrating a magnetometer and inertial measurement unit (IMU), focusing on balancing calibration accur
arXiv:2604.19028v1 Announce Type: new Abstract: One of the most challenging problems in graph machine learning is generalizing across graphs with diverse properties. Graph neural networks (GNNs) face
arXiv:2601.03442v4 Announce Type: replace-cross Abstract: Inspired by the success of performing multiple local optimization steps between communication rounds in federated learning, incorporating such
This post discusses an AI-generated image that is remarkably realistic with only minor flaws, specifically noting that the most noticeable error is a doubled hour hand on a clock face. Ethan Mollick u
A federal judge in Massachusetts struck down several Trump administration actions slowing down clean energy development, including a requirement that all solar and wind projects on federal lands and w
New Technical Report from @EkagraRanjan: Contrary to what you might expect, MoE-based LLMs make speculative decoding even more effective. Read more on our blog: Ever wondered how Speculative Decoding
arXiv:2604.18649v1 Announce Type: cross Abstract: As generative AI faces intensifying legal challenges, the machine learning community has increasingly relied on post-hoc mitigation -- especially mach
arXiv:2604.19684v1 Announce Type: new Abstract: Explainable artificial intelligence (XAI) has predominantly focused on generating model-centric explanations that approximate the behavior of black-box
arXiv:2508.01371v3 Announce Type: replace-cross Abstract: Smart contracts are important for digital finance, yet they are hard to patch once deployed. Prior work has mainly explored LLMs for smart con
arXiv:2509.05890v3 Announce Type: replace-cross Abstract: Quantum reinforcement learning has emerged as a framework combining quantum computation with sequential decision-making, and applications to t
arXiv:2503.16251v2 Announce Type: replace-cross Abstract: Federated Learning (FL) has gained prominence in machine learning applications across critical domains by enabling collaborative model trainin
arXiv:2604.19593v1 Announce Type: cross Abstract: The importance of clear and correct text in legal documents cannot be understated, and, consequently, a grammatical error correction tool meant to ass
arXiv:2604.19072v1 Announce Type: cross Abstract: Semi-supervised learning with manifold regularization is a classical framework for jointly learning from both labeled and unlabeled data, where the ke
This post discusses concerns about AI model degradation through the inclusion of low-quality or irrelevant training data, using butternut squash image generation as a humorous example of how excessive
arXiv:2604.19157v1 Announce Type: new Abstract: KV-cache memory is a major bottleneck in real-world LLM serving, where systems must simultaneously support latency-sensitive small-batch requests and hi
arXiv:2604.19489v1 Announce Type: new Abstract: This paper presents a computational case study that evaluates the capabilities of specialized machine learning models and emerging multimodal large lang
Reuters: SK Hynix says it plans to invest ~12.85B in a new fab in South Korea for advanced packaging to meet AI demand for HBM, with construction starting this month — SK Hynix (000660.KS) said on Wed
Financial Times: Sources: OpenAI has pledged up to 1.5B to a new joint venture with PE firms to help deploy AI across their portfolio companies, starting with 500M in equity — Start-up backing new com
As regulatory pressure intensifies and geopolitical uncertainty reshapes technology procurement, enterprises are rethinking control over their entire stack, with sovereign architectures emerging as th
arXiv:2602.00758v2 Announce Type: replace Abstract: Search-engine date filters are widely used to enforce pre-cutoff retrieval in retrospective evaluations of search-augmented forecasters. We show thi
This has in fact (at various levels) happened more than 1000 times. Check out @DamienCharlotin’s tracker and my substack essays about it. And it begins Sullivan & Cromwell just admitted to a federal j
arXiv:2604.19221v1 Announce Type: new Abstract: Full-duplex speech interaction, as the most natural and intuitive mode of human communication, is driving artificial intelligence toward more human-like
From vibe-coded and large-scale apps to AI models and agents, Cloud Run delivers on-demand compute with zero overhead and pay-per-use pricing for all of your workloads. Last year, the number of extern
This week at Google Cloud Next ‘26, we are sharing the evolution of Google Kubernetes Engine (GKE), delivering leading performance, efficiency, security, and scale for your most demanding and complex
Enterprises are locked in a long-term standoff with legacy infrastructure, with growing demand for virtualization modernization that doesn’t require a full rebuild. SUSE S.A. has positioned itself to
OpenAI has released workspace agents in research preview for ChatGPT Business, Enterprise, Edu, and Teachers subscription plans. Workspace agents are AI assistants designed to work within organization
Ethan Mollick discusses the concept of 'setting time on fire'—wasting time on unproductive activities—and explores the temptation to do so, drawing on arguments he originally published two years prior
Ethan Mollick defends his personal stylistic choice to use em-dashes in his writing, humorously asserting ownership of this distinctly human writing preference. The post appears to be a response to su
arXiv:2604.18570v1 Announce Type: cross Abstract: Modern medicine generates vast multimodal data across siloed systems, yet no existing model integrates the full breadth and temporal depth of the clin
arXiv:2604.16733v1 Announce Type: new Abstract: Physical awareness, especially in a large and dynamic environment, is shaped by sensing decisions that determine observability across space, time, and s
arXiv:2602.08129v2 Announce Type: replace-cross Abstract: Predicting interdependent load values in multiport scatterers is challenging due to high dimensionality and complex dependence between impedan
arXiv:2604.18151v1 Announce Type: new Abstract: Urban flooding is a growing climate change-related hazard in rapidly expanding African cities, where inadequate waste management often blocks drainage s
arXiv:2604.18398v1 Announce Type: new Abstract: Creativity has become a core competence in the era of LLMs and human-AI collaboration, underpinning innovation in real-world problem solving. Crucially,
arXiv:2604.17787v1 Announce Type: new Abstract: Precision-critical manipulation requires both global trajectory organization and local execution correction, yet most vision-language-action (VLA) polic
Ethan Mollick comments on an impressive AI model achievement, noting that the performance gap between models appears consistent with historical trends based on his assessment.
arXiv:2604.16675v1 Announce Type: new Abstract: Action recognition is a fundamental ability for social species. Yet, its underlying computations are not well understood. Classical psychophysical studi
arXiv:2510.19028v3 Announce Type: replace Abstract: As LLMs are increasingly deployed in real-world interactions, their social reasoning in interpersonal communication becomes critical. To explore the
arXiv:2603.26248v2 Announce Type: replace Abstract: Language endangerment poses a major challenge to linguistic diversity worldwide, and technological advances have opened new avenues for documentatio
arXiv:2604.16804v1 Announce Type: new Abstract: Optimization problems are central to decision-making in manufacturing, logistics, scheduling, and other industrial settings. Translating complicated des
Artificial intelligence and machine learning have been a central focus for Boomi LP over much of its 26 years as a data activation company. The organization began storing anonymized metadata from cust
arXiv:2604.17316v1 Announce Type: new Abstract: Safe clinical deployment of Large Language Models (LLMs) requires not only high accuracy but also robust uncertainty calibration to ensure models defer
arXiv:2603.23987v2 Announce Type: replace Abstract: Deploying clinical ML is slow and brittle: models that work at one hospital often degrade under distribution shifts at the next. In this work, we st
arXiv:2604.18184v1 Announce Type: new Abstract: Continuous Sign Language Recognition (CSLR) has achieved remarkable progress in recent years; however, most existing methods are developed under single-
This post likely discusses the challenges or difficulties of writing a sestina, the complex poetic form requiring six stanzas with a specific pattern of end-word repetition. Ethan Mollick, known for d