Knowledge catalogue
Clem Delangue highlights a significant development in local inference technology, noting that a project (referred to as 'whale bros') has released their work as open source. The post emphasizes the im
arXiv:2604.20886v1 Announce Type: cross Abstract: We present KinetiDiff, a structure-based framework for de novo kinase inhibitor design that integrates a Geometry-Complete Diffusion Model with real-t
arXiv:2508.10177v3 Announce Type: replace Abstract: Recent Large Language Model (LLM)-based AutoML systems demonstrate impressive capabilities but face significant limitations such as constrained expl
LangSmith for Startups Spotlight: @AdaptiveBuilds Adaptive is the AI-native project accounting platform built for construction. They embed AI agents directly into job costing, billing, and forecasting
arXiv:2604.21617v1 Announce Type: new Abstract: Parametric projections let analysts embed new points in real time, but input variations from measurement noise or data drift can produce unpredictable s
arXiv:2604.21897v1 Announce Type: new Abstract: Analyses of legislative behavior often rely on voting records, overlooking the rich semantic and rhetorical content of political speech. In this paper,
arXiv:2603.12845v2 Announce Type: replace Abstract: Predicting enzyme kinetic parameters quantifies how efficiently an enzyme catalyzes a specific substrate under defined biochemical conditions. Canon
arXiv:2510.20064v2 Announce Type: replace Abstract: Speculative decoding is widely used in accelerating large language model (LLM) inference. In this work, we focus on the online draft model selection
arXiv:2604.21253v1 Announce Type: cross Abstract: While LLMs demonstrate remarkable fluency in narrative generation, existing methods struggle to maintain global narrative coherence, contextual logica
Probably the most useful advice I can give you if you run an ad agency, a marketing company, a production studio, or anything in that space. Hear me out. I’ve spent a decade talking to teams about thi
arXiv:2604.21515v1 Announce Type: new Abstract: ASPIC-style structured argumentation frameworks provide a formal basis for reasoning in artificial intelligence by combining internal argument structure
arXiv:2604.20937v1 Announce Type: new Abstract: Video Large Language Models (Video LLMs) incur high inference latency due to a large number of visual tokens provided to LLMs. To address this, training
arXiv:2604.21043v1 Announce Type: cross Abstract: This paper examines the strategic use of language in contemporary artificial intelligence (AI) discourse, focusing on the widespread adoption of metap
arXiv:2604.21748v1 Announce Type: cross Abstract: Long-term conversational agents need memory systems that capture relationships between events, not merely isolated facts, to support temporal reasonin
arXiv:2604.21640v1 Announce Type: cross Abstract: Autonomous underwater vehicles are required to perform multiple tasks adaptively and in an explainable manner under dynamic, uncertain conditions and
These pelicans are kind of angry looking! Left is deepseek-v4-flash, right is deepseek-v4-pro - both generated using OpenRouter via my LLM tool 🚀 DeepSeek-V4 Preview is officially live & open-sourced!
arXiv:2604.02832v2 Announce Type: replace-cross Abstract: Accurate forecasting of recovery rates (RR) is central to credit risk management and regulatory capital determination. In many loan portfolios
arXiv:2604.21657v1 Announce Type: new Abstract: Machine learning methods that predict initial guesses from molecular geometry can reduce this cost, but matrix-prediction models fail when extrapolating
arXiv:2511.13587v2 Announce Type: replace-cross Abstract: Visual autoregressive (AR) generation models have demonstrated strong potential for image generation, yet their next-token-prediction paradigm
Ethan Mollick discusses the phenomenon of users entering deeply immersive, flow-like states while intensely interacting with advanced AI models, suggesting the need for better terminology to describe
arXiv:2604.19751v1 Announce Type: new Abstract: Generative AI is entering research, education, and professional work faster than current governance frameworks can specify how AI-assisted outputs shoul
arXiv:2604.20595v1 Announce Type: cross Abstract: We establish a mathematical correspondence between state space models, a state-of-the-art architecture for capturing long-range dependencies in data,
In this post, we'll explore how multimodal BioFMs work, showcase real-world applications in drug discovery and clinical development, and contextualize how AWS enables organizations to build and deploy
arXiv:2604.19925v1 Announce Type: cross Abstract: AI agents powered by large language models are increasingly acting on behalf of humans in social and economic environments. Prior research has focused
arXiv:2512.05070v2 Announce Type: replace-cross Abstract: Simulating the conditioned dynamics of diffusion processes, given their initial and terminal states, is an important but challenging problem i
arXiv:2604.20811v1 Announce Type: new Abstract: As LLMs are increasingly integrated into agentic systems, they must adhere to dynamically defined, machine-interpretable interfaces. We evaluate LLMs as
Enterprises are investing heavily in AI customer experience, but many experiments are stalling out before ever going live. The culprit is a confidence gap, according to Chris Mina (pictured), chief pr
arXiv:2506.23323v5 Announce Type: replace Abstract: Open-vocabulary semantic segmentation (OVSS) aims to segment objects from arbitrary text categories without requiring densely annotated datasets. Al
arXiv:2407.09577v4 Announce Type: replace Abstract: Normalization layers are ubiquitous in large language models (LLMs) yet represent a compute bottleneck: on hardware with distinct vector and matrix
Healthcare has long operated in data silos — payers, providers and patients each holding fragmented pieces of the same clinical story. That fragmentation, once accepted as the cost of doing business,
arXiv:2604.20157v1 Announce Type: new Abstract: Recent advances in model architectures, compute, and data scale have driven rapid progress in video generation, producing increasingly realistic content
arXiv:2508.18168v3 Announce Type: replace Abstract: Retrieval-augmented generation (RAG) has become a widely recognized paradigm to combine parametric memory with non-parametric memories. An RAG model
arXiv:2511.17069v3 Announce Type: replace Abstract: AI-driven automated scoring systems offer scalable and efficient means of evaluating complex student-generated responses. Yet, despite increasing de
arXiv:2511.11931v2 Announce Type: replace Abstract: This paper proposes MATT-Diff: Multimodal Active Target Tracking by Diffusion Policy, a control policy for active multi-target tracking using a mobi
arXiv:2601.07476v2 Announce Type: replace Abstract: Autonomous nano-drones, powered by vision-based tiny machine learning (TinyML) models, are a novel technology gaining momentum thanks to their broad
arXiv:2604.20733v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a core post-training recipe. Introducing suitable off-policy trajectories into on-polic
arXiv:2604.19800v1 Announce Type: cross Abstract: This paper presents a detailed study of how graph neural networks can be used on edge intelligent meters in a microgrid to forecast photovoltaic power
arXiv:2510.09574v2 Announce Type: replace Abstract: Autonomous navigation in unfamiliar environments requires robots to simultaneously explore, localise, and plan under uncertainty, without relying on
arXiv:2604.19795v1 Announce Type: new Abstract: We introduce prism{} (extbf{P}robabilistic extbf{R}etrieval with extbf{I}nformation-extbf{S}tratified extbf{M}emory), an evolutionary memory substrate f
arXiv:2604.20000v1 Announce Type: new Abstract: Automated wildlife monitoring from aerial imagery is vital for conservation but remains limited by two persistent challenges: the difficulty of detectin
arXiv:2604.20730v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have shown promising capabilities in generating Scalable Vector Graphics (SVG) via direct code synthesis. Howev
Salesforce Inc. said today it’s trying to break down the siloes that separate enterprise’s customer relationship management data from their productivity tools, specifically for artificial intelligence
arXiv:2604.20039v1 Announce Type: new Abstract: Causal discovery through experimentation and intervention is fundamental to robust problem solving. It requires not just updating beliefs within a fixed
This article by Ethan Mollick likely discusses emerging capabilities and implications of GPT-5.5, OpenAI's next-generation language model, exploring how it represents advancement in AI technology and
arXiv:2604.20395v1 Announce Type: new Abstract: Open-vocabulary 3D instance segmentation is a core capability for robotics and AR/VR, but prior methods trade one bottleneck for another: multi-stage 2D
arXiv:2604.20158v1 Announce Type: new Abstract: Enterprise deployment of long-horizon decision agents in regulated domains (underwriting, claims adjudication, tax examination) is dominated by retrieva
🎙️ Talked to @ListenLabs co-founder + CTO @florian_jue in the latest Max Agency. Really enjoyed hearing about the architectural decisions behind their agents, their self-reviewing feedback subagents,
arXiv:2509.21267v3 Announce Type: replace Abstract: Large language models often generate homogeneous outputs, but whether this is problematic depends on the specific task. For objective math tasks, re
arXiv:2604.19757v1 Announce Type: cross Abstract: This paper presents a transparent screening framework for estimating inference and training impacts of current large language models under limited obs
arXiv:2604.19801v1 Announce Type: cross Abstract: Automatic Speech Recognition (ASR) is increasingly used in applications involving child speech, such as language learning and literacy acquisition. Ho
arXiv:2601.17609v2 Announce Type: replace Abstract: In domains like medicine and finance, large-scale labeled data is costly and often unavailable, leading to models trained on small datasets that str
arXiv:2508.16676v2 Announce Type: replace-cross Abstract: Transformer architecture gradually dominates the LLM field. Recent advances in training optimization for Transformer-based large language mode
Worth a read if you are building production-grade AI agents. // Stateless Decision Memory for Enterprise AI Agents // Most of the interesting AI agent papers right now are about capability. This one i
arXiv:2603.27889v2 Announce Type: replace Abstract: Framing theory posits that how information is presented shapes audience responses, but computational work has largely ignored audience reactions. Wh
arXiv:2604.19618v1 Announce Type: new Abstract: Reliable pipeline inspection is critical to safe energy transportation, but is constrained by long distances, complex terrain, and risks to human inspec
arXiv:2512.19302v2 Announce Type: replace Abstract: Large Vision--Language Models (LVLMs) hold great promise for advancing optical remote sensing (RS) analysis, yet existing reasoning segmentation fra
arXiv:2604.19488v1 Announce Type: new Abstract: Large language models (LLMs) have achieved substantial advances in logical reasoning, yet they continue to lag behind human-level performance. In-contex
arXiv:2604.19141v1 Announce Type: new Abstract: Diffusion- and flow-based models usually allocate compute uniformly across space, updating all patches with the same timestep and number of function eva
arXiv:2604.18788v1 Announce Type: new Abstract: Apple Neural Engine (ANE) is a dedicated neural processing unit (NPU) present in every Apple Silicon chip. Mixture-of-Experts (MoE) LLMs improve inferen
arXiv:2507.01918v3 Announce Type: replace-cross Abstract: We develop a rotation-invariant neural network that provides the global minimum-variance portfolio by jointly learning how to lag-transform hi