Knowledge catalogue
Big release here! Async subagents will become more and more of a thing, as subagents get longer running and you don’t want to block the event loop 🚀 deepagents 0.5 release 👉 Async subagents - kick off
arXiv:2604.09938v1 Announce Type: cross Abstract: Conventional field operations spend most of their energy moving the tractor body, not the implement. Yet feasibility studies for novel agricultural ve
arXiv:2604.10900v1 Announce Type: new Abstract: In large language models performing long-form reasoning, the KV cache grows rapidly with decode length, creating bottlenecks in memory and inference sta
arXiv:2604.10973v1 Announce Type: new Abstract: Reasoning over tabular data is a crucial capability for tasks like question answering and fact verification, as it requires models to comprehend both fr
arXiv:2604.09611v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in applications forming multi-request workflows like document summarization, search-based copilots,
arXiv:2604.11251v1 Announce Type: new Abstract: Training language-conditioned whole-body controllers for humanoid robots requires large-scale datasets pairing motion trajectories with natural-language
arXiv:2604.10352v1 Announce Type: new Abstract: Stateful tool-using LLM agents treat the context window as working memory, yet today's agent harnesses manage residency and durability as best-effort, c
arXiv:2604.11641v1 Announce Type: cross Abstract: Code agents are advancing rapidly, but debugging them is becoming increasingly difficult. As frameworks orchestrate parallel tool calls and multi-stag
arXiv:2501.18490v3 Announce Type: replace-cross Abstract: This article introduces a novel sample-efficient curriculum learning (CL) approach for training an end-to-end reinforcement learning (RL) poli
arXiv:2604.11206v1 Announce Type: cross Abstract: Digital nudging systems lack architectural guidance for translating behavioral science into software design. While research identifies nudge strategie
arXiv:2604.09920v1 Announce Type: new Abstract: Vision foundation models (VFMs) offer the promise of zero-shot object detection without task-specific training data, yet their performance in complex ag
arXiv:2604.09606v1 Announce Type: new Abstract: Traditional benchmarks for large language models (LLMs), such as HELM and AIR-BENCH, primarily assess safety risk through breadth-oriented evaluation ac
arXiv:2604.10991v1 Announce Type: cross Abstract: The growing use of generative artificial intelligence (AI) in academic writing has raised increasing concerns regarding transparency and academic inte
arXiv:2604.09582v1 Announce Type: new Abstract: Factorizing datasets is an interesting process in a multitude of approaches, but many times it is not possible or efficient the computation of a factori
arXiv:2604.11556v1 Announce Type: cross Abstract: LLM-assisted software development has become increasingly prevalent, and can generate large-scale systems, such as compilers. It becomes crucial to st
arXiv:2604.10512v1 Announce Type: new Abstract: The development of generalizable Novel View Synthesis (NVS) models is critically limited by the scarcity of large-scale training data featuring diverse
arXiv:2604.11378v1 Announce Type: new Abstract: The dominant paradigm for building LLM based agents is the Agent Loop, an iterative cycle where a single language model decides what to do next by readi
arXiv:2604.10300v1 Announce Type: cross Abstract: LLM-based coding agents are increasingly used to generate code, tests, and documentation. Still, their outputs can be plausible yet misaligned with de
Understanding the relationships within your data is crucial for uncovering hidden insights and building intelligent applications. However, managing operational (OLTP) and analytical (OLAP) graph workl
arXiv:2604.11104v1 Announce Type: new Abstract: This paper presents an empirical study of a multi-model zero-shot pipeline for knowledge graph construction and exploitation, executed entirely through
arXiv:2604.10658v1 Announce Type: new Abstract: Institutional decisions -- regulatory compliance, clinical triage, prior authorization appeal -- require a different AI architecture than general-purpos
arXiv:2604.10385v1 Announce Type: new Abstract: Generating complex multi-actor scenario videos remains difficult even for state-of-the-art neural generators, while evaluating them is hard due to the l
arXiv:2604.09631v1 Announce Type: cross Abstract: As deep learning models are deployed on resource constrained edge platforms in autonomous driving systems, reli able knowledge of hardware behavior un
arXiv:2604.09579v1 Announce Type: new Abstract: In large-scale cloud service platforms, thousands of customer tickets are generated daily and are typically handled through on-call dialogues. This high
A Reddit post on r/ChatGPT in which a developer shares a Telegram bot they built specifically to engage with and study the behavior of online scammers for research purposes, and seeks volunteer tester
I had such a great time at @aiDotEngineer Europe last week ! Except for one thing: My workshop went terribly because I vibe-slopped a little bit too hard half an hour before it started and was too fra
arXiv:2604.11035v1 Announce Type: new Abstract: Diffusion language models promise parallel generation, yet still lag behind autoregressive (AR) models in quality. We stem this gap to a failure of intr
A Reddit post from r/ChatGPT in which a practitioner claims experience building AI prompt systems for real-world investment research shares five common mistakes investors make when using AI for financ
arXiv:2603.11346v2 Announce Type: replace Abstract: Humanoid robotics has strong potential to transform daily service and caregiving applications. Although recent advances in general motion tracking w
arXiv:2604.09635v1 Announce Type: cross Abstract: This study develops machine learning models to assess Media and Information Literacy (MIL) skills specifically in the context of disinformation among
arXiv:2604.02600v2 Announce Type: replace-cross Abstract: Developing a novel research idea is hard. It must be distinct enough from prior work to claim a contribution while also building on it. This r
arXiv:2604.11188v1 Announce Type: cross Abstract: Synthesizing high-quality mathematical reasoning data without human priors remains a significant challenge. Current approaches typically rely on seed
arXiv:2408.11871v4 Announce Type: replace-cross Abstract: Fake news significantly influences decision-making processes by misleading individuals, organizations, and even governments. Large language mo
arXiv:2510.24168v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have significantly advanced GUI agents, yet long-horizon automation remains constrained by two critical bot
arXiv:2604.09744v1 Announce Type: cross Abstract: The AI agent ecosystem has converged on two protocols: the Model Context Protocol (MCP) for tool invocation and Agent-to-Agent (A2A) for single-princi
arXiv:2604.10401v1 Announce Type: new Abstract: Inferring nationality from personal names is a critical capability for equity and bias monitoring, personalization, and a valuable tool in biomedical an
NVIDIA NVbandwidth is a performance analysis tool designed to measure memory bandwidth and latency between various components in GPU-equipped systems, providing detailed measurements of data transfer
arXiv:2604.09795v1 Announce Type: cross Abstract: This paper investigates a planar tracking problem between a leader and follower agent. We propose a novel feedback speed control law, paired with a co
one-shot podcast from news with @flymy_ai's new agent builder (just tested it), it: - researched news - created a transcript - created a voice for each part - stitched it together full prompt + output
arXiv:2604.10087v1 Announce Type: new Abstract: We present EL-DRUIN, an ontological reasoning system for geopolitical intelligence analysis that combines formal ontology, finite semigroup algebra, and
arXiv:2604.09580v1 Announce Type: new Abstract: Standard Chain-of-Thought (CoT) prompting empowers Large Language Models (LLMs) with reasoning capabilities, yet its reliance on linear natural language
arXiv:2604.09791v1 Announce Type: new Abstract: Small language models are attractive for production deployment due to their low cost, fast inference, and ease of specialization. However, adapting them
arXiv:2604.10812v1 Announce Type: new Abstract: Pokemon Red is a long-horizon JRPG with sparse rewards, partial observability, and quirky control mechanics that make it a challenging benchmark for rei
arXiv:2508.19600v2 Announce Type: replace Abstract: Post-training quantization (PTQ) is crucial for deploying efficient object detection models, like YOLO, on resource-constrained devices. However, th
arXiv:2604.09548v1 Announce Type: cross Abstract: Older adults commonly experience chronic conditions such as pain and sleep disturbances and may consider cannabidiol for symptom management. Safe use
arXiv:2505.15489v4 Announce Type: replace-cross Abstract: The impact of multimodal misinformation arises not only from factual inaccuracies but also from the misleading narratives that creators delibe
arXiv:2512.18682v2 Announce Type: replace Abstract: In the high-cost simulation-driven design domain, translating ambiguous design requirements into a mathematical optimization formulation is a bottle
arXiv:2604.11805v1 Announce Type: cross Abstract: We have witnessed remarkable advances in LLM reasoning capabilities with the advent of DeepSeek-R1. However, much of this progress has been fueled by
arXiv:2604.10833v1 Announce Type: cross Abstract: Recent reports indicate that sustained interaction with conversational artificial intelligence (AI) systems can, in a small subset of users, contribut
arXiv:2604.09557v1 Announce Type: cross Abstract: Speculative Decoding (SD) has emerged as a critical technique for accelerating Large Language Model (LLM) inference. Unlike deterministic system optim
arXiv:2604.09553v1 Announce Type: cross Abstract: LLM development has aroused great interest in Sequential Recommendation (SR) applications. However, comprehensive evaluation of SR models remains lack
arXiv:2604.09737v1 Announce Type: cross Abstract: Structured prediction requires models to generate ontology-constrained labels, grounded evidence, and valid structure under ambiguity, label skew, and
arXiv:2604.09562v1 Announce Type: cross Abstract: Efficient LLM serving must balance throughput and latency across diverse, bursty workloads. We introduce StreamServe, a disaggregated prefill decode s
arXiv:2604.09706v1 Announce Type: cross Abstract: Recent AI media detectors report near-perfect performance under clean laboratory evaluation, yet their robustness under realistic deployment condition
arXiv:2604.09614v1 Announce Type: new Abstract: This paper develops a measure-theoretic framework establishing when and how a possibilistic representation of incomplete knowledge contracts into a prob
This Reddit post argues that AI's most practical and immediate value lies not in replicating or surpassing human intelligence, but in serving as a tool for cognitive offloading — handling mentally tax
This is the episode all early-stage devtool founders should listen to. We were very lucky to have @amirrustam as a guest in our podcast, Dev Propulsion Labs. He's a partner at @Firestreakvc with many
arXiv:2604.11077v1 Announce Type: new Abstract: Customer service chatbots are increasingly expected to serve not merely as reactive support tools for users, but as strategic interfaces for harvesting
arXiv:2506.05014v2 Announce Type: replace-cross Abstract: We propose a novel, flexible, and efficient framework for designing Concept Bottleneck Models (CBMs) that enables practitioners to explicitly
arXiv:2604.11564v1 Announce Type: new Abstract: Single-image super-resolution has progressed from deep convolutional baselines to stronger Transformer and state-space architectures, yet the correspond