Measures how well LLMs and agent-driven workflows prepare supervised training data end-to-end by jointly benchmarking data construction and data-quality evaluation across six domains, using a downstream-grounded protocol and new metrics.
Provides page-level relevance judgments and full OCR'd annual-report text for KPI question answering and page retrieval benchmarking — supports retrieval (per-page qrels) and needle‑in‑a‑haystack numeric extraction over long documents, with eval and train configs.
Pairs OCR-extracted annual-report text with ground-truth financial KPI values to benchmark LLM/table-QA and needle-in-a-haystack extraction tasks. Includes Markdown OCR (.mmd), page images for eval, and 31 KPI columns across multiple years—suited for KPI extraction, retrieval, and robustness testing.
Self‑hosted A‑share quantitative workbench for screening, monitoring, backtesting and stock-level analysis using TickFlow data; supports 18 Polars strategies, vectorbt backtesting, realtime rule-based alerts, pluginable data sources and optional LLM-driven strategy generation and stock analysis.
Provides multi-turn tool-calling examples grounded in SEC filings for fine-tuning financial reasoning agents, covering tasks such as numerical reasoning, financial modeling, and market analysis.
Provides a public test split of multimodal financial GUI interaction examples for evaluating agents that convert instructions and screenshots into grounded UI actions. Includes step-level screenshots, dialogue history, an OpenAI-style computer_use tool schema, and JSON next-action references; training data available on request.
Aggregates multiple free public market endpoints into a self‑hosted, terminal‑style web trading workspace: live quotes, candlesticks, screener, options, crypto, portfolio tracking and an optional Claude AI assistant. No paid API keys and automatic provider fallbacks.
Evaluates multimodal context learning across grounding, new information application, and knowledge acquisition using a 3,443-instance benchmark spanning science, finance, long documents, spatial reasoning, and web VQA; finds current multimodal models perform poorly (best score 0.2847) and analyzes failure modes.
Evaluates whether long-horizon agents can complete real-world business requests while preserving valid intermediate execution. Built from 50 multi-turn payment workflows with 789 knowledge documents and 601 discoverable tools, and uses deterministic checks for process and protection violations.