Large-scale pretrained models for goal-directed dialog
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Updated
Dec 10, 2023 - Python
Large-scale pretrained models for goal-directed dialog
Open-vocabulary Object Segmentation with Diffusion Models
This is a list of open-source projects at Microsoft Research NLP Group
Statewave use case in TypeScript: a grounded product advisor and support assistant, with an Ops Assistant that tracks and closes content gaps.
Deterministic multi-LLM orchestration with grounded, verified answers, an editable guardrail gate, and a live process dashboard.
Conversational + predictive crime intelligence on Zoho Catalyst: ask 1M+ FIRs in English or Kannada and see the query and rows behind every answer. All-India NCRB-calibrated corpus (640 districts), forecasting validated on 6.37M real incidents, and a trilingual WhatsApp channel for field officers.
Beginner-friendly Python RAG project that turns StackOverflow Q&A data into a grounded knowledge assistant using sentence-transformer embeddings, FAISS retrieval, and strict citation-based LLM answering.
Levi's RAG is an AI due diligence copilot for equity research on Levi Strauss & Co. It answers natural-language financial questions using only official SEC filings, grounding each answer in the exact source sentence and tagging it with an evidence tier (verified, qualitative, benchmark, or inference).
ComfyUI Custom Nodes for Gen Searcher and other tools
An open-source LLM for food product development
Secure Enterprise RAG platform with RBAC enforcement, OWASP LLM defenses, hybrid retrieval, grounded generation, explainability, and zero-trust context pipelines.
Dependency-free checks for structured local-model output, grounded answers, citations, and protected writes.
Grounded-or-silent reference assistant for public agencies: answers only from a supplied corpus, cites every claim, and refuses cleanly rather than guessing. No model and no network at answer time. English and Spanish plus right-to-left languages. A reference implementation to read, not a product to deploy.
Financial report grounded QA post-training with QLoRA SFT, DPO preference learning, citation/numeric evaluation, and badcase analysis.
Developer-first prompt engineering patterns for grounded, testable, and reliable AI outputs.
Strictly-grounded RAG chat on Adobe Spectrum docs — a native react-instantsearch (useChat) frontend on Algolia Agent Studio + an Algolia index. Per-answer grounding judge (3-judge corroboration-gate panel) as a Confidence chip → breakdown drawer. Reusable Algolia-Central-[company] template.
Turn research PDFs into grounded Markdown drafts — driven by any token-free AI coding-agent session (Claude, Codex, Gemini, Copilot, Cursor, Amp, Crush, Goose, Grok) when online, local Ollama when offline.
Turn a product idea into a grounded, buildable SRD suite — a skills.sh agent skill
Grounded RAG v1 specification with abstain/partial semantics
AI-powered research assistant that plans multi-query searches, retrieves and verifies web sources, and synthesizes grounded, cited reports built with FastAPI, Gemini, and React.
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