LLM-agents are increasingly used to accelerate the progress of scientific research. Yet a persistent bottleneck is data access: agents not only lack readily available tools for retrieval, but also have to work with unstrcutured, human-centric data on...
Recent advances in Large Language Models (LLMs) allow agents to execute complex natural language tasks. Many LLM applications, such as support agents, teaching assistants, and interactive bots, involve multi-turn conversations. However, it remains ch...
Deploy teams of AI agents in your projects to execute multiple tasks concurrently.
Build AI teams that think, learn, and act. Custom AI Agents are the Intelligence layer of your Workspace DNA. They reason over your project data, connect to 100+ integrations via MCP connectors, and …
Vibe code AI apps, deploy agents, and automate workflows from one prompt. Living software with Workspace DNA - memory, intelligence, and execution in one platform. Start free.
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Imagine doctors with digital sidekicks or hospitals running on code: in a few years, that could be reality. By 2025, **AI agents** – smart software that plans, decides, and acts on medical data – ...
The integration of conversational agents into our daily lives has become increasingly common, yet many of these agents cannot engage in deep interactions with humans. Despite this, there is a noticeable shortage of datasets that capture multimodal in...
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An open, platform-agnostic list of user-agent and referrer regexes for use in podcast analytics services (⭐ 124)
In Pico Rivera, CA, ICE agents rolled up to a Walmart with **rifles out and tactical gear** to arrest a janitor. Adrian Andrew Martinez, a **20-year-old U.S. citizen**, witnessed it and **tried to in...
Feb 26, 2026 · But I keep thinking about something. Are AI agents actually improving product discovery on Product Hunt or are they just making launches look more polished? Yes, AI speeds things up. …
This technical report presents our 1st place solution for the Waymo Open Sim Agents Challenge (WOSAC) 2023. Our proposed MultiVerse Transformer for Agent simulation (MVTA) effectively leverages transformer-based motion prediction approaches, and is t...
Embodied agents face significant challenges when tasked with performing actions in diverse environments, particularly in generalizing across object types and executing suitable actions to accomplish tasks. Furthermore, agents should exhibit robustnes...
LLM-based coding agents are increasingly common but still face challenges in context management, latency, reliability, reproducibility, and scalability. We present Agint, an agentic graph compiler, interpreter, and runtime that incrementally and hier...
Mar 6, 2024 · Dear ringThis is now the 4-5 time my alarm has falsely trigger 5 or so minutes after arming and leaving. I called today and the very unprofessional agents accent was difficult to understand. As …
We study a neuro-inspired model that mimics a discussion (or information dissemination) process in a network of agents. During their interaction, agents redistribute activity and network weights, resulting in emergence of leader(s). The model is able...
We introduce DRBench, a benchmark for evaluating AI agents on complex, open-ended deep research tasks in enterprise settings. Unlike prior benchmarks that focus on simple questions or web-only queries, DRBench evaluates agents on multi-step queries (...
This paper proposes a strategy to estimate the velocity and position of neighbor agents using distance measurements only. Since with agents executing arbitrary motions, instantaneous distance-only measurements cannot provide enough information for ou...
We study four NP-hard optimal seat arrangement problems [Bodlaender et al., 2020a], which each have as input a set of n agents, where each agent has cardinal preferences over other agents, and an n-vertex undirected graph (called seat graph). The tas...