How We Took Over ChatGPT Accounts Parameter Labs describe an exploit they found against ChatGPT's implementation of the artifacts pattern (OpenAI used to call this "Canvas" but it looks like the latest revision is cal... Context & related coverage →
How I Built the Most AI-Pilled Company in the World Don't be put off by the clickbait headline, this piece by Jacob Sansbury describing how they are building Spawn is a fascinating exploration of the bleeding edge of... Context & related coverage →
arxiv.org · 2026-10-29 · Ranked: agent + eval match · research watch · fresh 0.70 · score 2.03
Complex information seeking on the Web often requires collecting evidence from multiple documents and reasoning across them, as in multi-hop question answering. Multi-agent systems address such tasks by dividing work... Context & related coverage →
arxiv.org · 2026-10-29 · Ranked: agent match · research watch · fresh 0.66 · score 2.03
When one AI agent tells another that "the tests passed" or "a person approved this refund", the receiver has only the sender's word. A2A and MCP authenticate the channel, but the sender is the party in doubt, so a pro... Context & related coverage →
arxiv.org · 2026-10-29 · Ranked: agentic + evaluation match · research watch · fresh 0.72 · score 2.01
Building and scaling computer-using agents (CUAs) across desktop, mobile, and web environments requires reliable task-completion verification for data curation, evaluation, and reinforcement learning. Typical automate... Context & related coverage →
The Google Cloud AI Infrastructure team had another busy month in October, filled with new product launches and updates to power today’s AI and agentic workloads scalably and efficiently. We were also honored to share... Context & related coverage →
arxiv.org · 2026-10-29 · Ranked: agent + eval match · research watch · fresh 0.72 · score 1.94
How effectively can vision-language-action (VLA) models learn diverse language-conditioned behaviors as training data scales? Investigating this question requires large and varied robot datasets, whose collection on p... Context & related coverage →
arxiv.org · 2026-10-29 · Ranked: evaluation match · research watch · fresh 0.72 · score 1.93
Sparse mixture-of-experts (MoE) models expand parameter capacity by activating a small subset of experts per token. Expert selection directly affects model capabilities under a fixed active-expert budget. Dense evalua... Context & related coverage →
A new decoy counting benchmark exposes a gap between seeing and reasoning. Elorian’s Glimpse tries to bridge it by thinking with images. Context & related coverage →
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