Paper

WebSwarm: a progressive recursive multi-agent system for deep-and-wide web search

WebSwarm is a new multi-agent web search system that addresses the limitations of single ReAct-style agents in handling deep and wide search tasks. It uses progressive recursive collaboration among agents to improve depth, coverage, and evidence-grounded expansion. The system is described in a paper posted on arXiv on July 9, 2026.

0 engagement·1 source·Thu, Jul 9, 2026, 04:28 PM

The paper introduces WebSwarm, a multi-agent orchestration framework for deep-and-wide web search. It overcomes the constraints of single ReAct-style agents, which are limited by long trajectories and context windows. Existing multi-agent systems improve coverage via parallel execution but lack recursive depth and adaptive collaboration. WebSwarm employs progressive recursive collaboration to enhance search depth, coverage, and evidence-grounded expansion. The system is designed for complex, research-oriented information seeking tasks.

Entities

WebSwarm(tool)ReAct(concept)arXiv(tool)

Tool ReleaseSat, Jul 11, 2026, 04:49 PM

Developer creates standalone SearXNG CLI+MCP for open-source coding agents

A developer built a standalone SearXNG CLI and MCP tool that enables open coding agents (like OpenCode, pi coding agent) to perform agentic web search without relying on proprietary APIs or running SearXNG as a standalone Python service. The tool is portable and harness-independent, addressing a key limitation in open-source coding agents.

1 engagement·1 source·hackernews

BenchmarkThu, Jul 9, 2026, 05:59 PM

UniClawBench benchmark proposed for evaluating proactive AI agents in real-world tasks

Researchers introduced UniClawBench, a universal benchmark for evaluating proactive agents that operate everyday tools in real-world environments. Unlike existing benchmarks that rely on sandboxed settings and single-turn evaluations, UniClawBench aims to isolate specific model capabilities to identify root causes of agent failures.

0 engagement·1 source·arxiv

arXiv

ProductSat, Jul 11, 2026, 11:57 PM

Collection of 48 working AI agent examples in Python and TypeScript

A curated repository of 48 functional AI agent implementations covering common patterns like research, code review, SQL, data analysis, and web scraping. Each example is designed to be cloned and run immediately, solving the problem of broken or incomplete agent tutorials for developers building AI systems.

3 engagement·1 source·reddit

ProductSun, Jul 12, 2026, 05:51 AM

Replay coding-agent sessions on a 3D codebase map

Mindwalk replays coding-agent sessions on a 3D map of your codebase, letting developers visualize and debug agent actions spatially. It uses LLMs to power the coding agent whose sessions are replayed, helping developers understand agent behavior and codebase structure.

4 engagement·1 source·hackernews

PaperSun, Jul 12, 2026, 08:50 AM

Researcher seeks arXiv endorsement for multi-agent citation verification framework

A researcher is seeking an arXiv endorsement for a paper proposing a four-agent framework built on CrewAI that addresses hallucinated citations in LLM-generated literature reviews. The framework includes an Academic Retriever, Critical Reviewer, Technical Writer, and Editor/Verifier implementing claim-level citation verification.