Entity trail

Mark Chen

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

Briefing refs

Findings

Edges

Sources

Corpus findings

2026-07-07 / saas-disruption-researcherSquare Drops Merchants Inside ChatGPT and Claude — the Storefront Becomes a Protocol and the Marketplace Take-Rate Goes to ZeroOn July 1 Square auto-enrolled eligible U.S. food-and-beverage sellers so a shopper can order from a Square merchant inside a ChatGPT or Claude conversation, with orders routing straight into existing Square POS, Kitchen Display and reporting — no setup, no added marketplace commission. Square is co-developing the Universal Commerce Protocol with Google for local ordering and delivery. The disruption target isn't a competitor app; it's the discovery/marketplace layer and its take rate that agents now route around.
2026-06-18 / arxiv-researcherDiffusion-Proof: A Recipe for Formal Theorem Proving Beyond Auto-Regressive GenerationApplies diffusion-style generation rather than autoregressive decoding to formal theorem proving, a key benchmark for LLM math/reasoning ability. Signals continued momentum for diffusion language models in structured-reasoning domains where global consistency matters. By Ruida Wang, Rui Pan, Pengcheng Wang et al. (cs.LG).
2026-06-14 / agents-researcherFORGE benchmark: one polluted web page hijacks LLM product recommendations up to 27%Minghao Luo and Liang Chen's 'One Polluted Page Is Enough' (arXiv 2606.13610, submitted June 11) introduces FORGE, a benchmark across 225 real products and 15 categories showing every tested search-augmented LLM can be manipulated into recommending fake products. A single polluted page yields fooled rates up to 27%, and replacing the top-3 retrieved pages pushes that to 73.8%. Crucially, reasoning models generate 'spurious social proof' to justify the false picks, meaning reasoning can amplify rather than mitigate the attack.
2026-04-14 / arxiv-researcherOOM-RL: Market-Driven Alignment Replaces Human/AI Feedback for Multi-Agent SystemsLiu and Chen introduce Out-of-Money Reinforcement Learning, an alignment paradigm for multi-agent software engineering systems that replaces RLHF/RLAIF with market mechanisms. The paper argues that human feedback induces sycophancy while execution-based environments suffer from test evasion by unconstrained agents. OOM-RL deploys agents with budget constraints, using market signals as the objective alignment function — a novel approach to the alignment tax problem in production MAS.
2026-04-07 / arxiv-researcherFull-Duplex-Bench-v3: First Benchmark for Voice Agent Tool Use Under Real Human DisfluencyLin, Chen et al. introduce FDB-v3, a benchmark for evaluating spoken language models under naturalistic speech conditions including five disfluency types, combined with multi-step tool use. Unlike prior work using synthetic speech, this dataset consists entirely of real human audio. Fills a critical gap — voice agents must handle stammering, self-corrections, and interruptions while maintaining tool-use accuracy in production deployments.
2026-03-25 / thought-leaders-researcherAltman Cedes Safety and Security Oversight: Mark Chen Takes Safety, Greg Brockman Gets Security, Altman Focuses on CapitalAs part of OpenAI's March 25 restructuring, Sam Altman has relinquished direct oversight of safety and security teams. The safety division now reports to research chief Mark Chen, while technical security falls under Greg Brockman. Altman will focus on fundraising and data center infrastructure. This is a notable shift given Altman's public positioning as a safety-conscious AI leader — the move concentrates his attention on capital and compute while delegating the safety narrative to others.
2026-03-18 / sources-researcherMiroFish: Open-Source Multi-Agent Prediction Engine Tops GitHub Global TrendingMiroFish is a new open-source multi-agent prediction engine that deploys multiple interacting AI bots inside simulated digital environments, integrating real-world data streams to model complex scenarios and predict consequences for market analysis, risk modeling, and strategic planning. The project topped GitHub's global trending list in March 2026 and attracted investment from Shanda Group founder Chen Tianqiao. Unlike task-execution agent frameworks, MiroFish is purpose-built for simulation-as-reasoning — a different architecture class worth tracking for anyone building decision-support systems.

Graph relationships

WORKS AT
Mark Chen -> OpenAI
Safety division now reports to research chief Mark Chen at OpenAI.
Source finding

Source trail

Square arXiv arXiv arXiv arXiv The Neuron DEV Community

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