Proof pending. This topic has not reached the minimum paper threshold yet.
Diagnosing failures in LLM agents remains largely manual. Practitioners inspect a small subset of execution traces, form ad-hoc hypotheses, and iterate. This process misses patterns that only emerge a...
Large language models (LLMs) have demonstrated remarkable capabilities in function calling for autonomous agents, yet current mechanisms lack explicit reasoning transparency during parameter generatio...
Recent advances in unified multimodal models (UMMs) have led to a proliferation of architectures capable of understanding, generating, and editing across visual and textual modalities. However, develo...
Freshness
Canonical route: /topics
Agent Handoff
Canonical ID ai-tooling | Route /topic/ai-tooling
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/topic/ai-toolingMCP example
{
"tool": "search_papers",
"arguments": {
"query": "AI Tooling",
"cluster": "AI Tooling"
}
}source_context
{
"surface": "topic",
"mode": "topic",
"query": "AI Tooling",
"normalized_query": "ai-tooling",
"route": "/topic/ai-tooling",
"paper_ref": null,
"topic_slug": "ai-tooling",
"benchmark_ref": null,
"dataset_ref": null
}Use This Via API or MCP
Topic pages bundle paper counts, viability trends, author concentration, and top questions into one canonical surface your agents can reference before they open Signal Canvas or create a workspace.