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Orchestrator-Workers + Augmented Function-Calling + Agent Loop: The Combination Nobody's Tried
Three agent-design patterns exist separately in the literature — task-decomposing orchestrators, tool-augmented reasoning, and iterative loops with escalation. Nobody has combined all three with fine-tuning specifically for working inside that loop. This is the general framing; the financial-LLM post is one worked instance of it.
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Sector-Specialized Financial LLMs: Filing Evidence, Calculation Tools, and Verifiable Reasoning
A research-framing post: why nobody has combined fine-tuning, an agent loop, and escalation for evidence-grounded financial reasoning — and the two open questions that matter most (a chain-of-thought method for tool-verifiable calculation, and how to generate training data for it).
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Chain-of-Goals: latent chain-of-thought for long-horizon offline RL
A review of CoGHP (arXiv 2602.03389), read as a case study in *internal* chain-of-thought: latent subgoals as reasoning steps inside a single autoregressive control policy — the big problem, the method, the honest numbers, and where it points.
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VLA models through the lens of adaptation
A survey-first deep dive into vision-language-action models, organized around the one axis that actually measures progress — adaptation across bodies, tasks, action spaces, and distributions — with Qwen-VLA as the worked case.
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Qwen-VLA — one model for manipulation, navigation, and trajectory
Deep reading note on Qwen-VLA (arXiv 2605.30280): a Qwen3.5-4B VLM backbone + a 1.15B DiT flow-matching action decoder, unified across tasks, environments, and robot embodiments via embodiment-aware prompt conditioning.