Scholar — AI & ML Research Digests
Literature digests on 6 active research areas including LLM Agents & Planning, Retrieval-Augmented Generation, AI Alignment & Safety. Real papers via the AISA Scholar API, synthesized for fast comprehension.
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Fast-read literature digests across active AI/ML research areas — each grounded in real papers from academic search and synthesized for agents and researchers.
LLM Agents & Planning: Literature Digest
10 papers
Large language model agents planning: A literature digest Recent work on large language model (LLM) agents planning has …
Retrieval-Augmented Generation: Research Digest
10 papers
Literature Digest: Retrieval‑Augmented Generation Retrieval‑augmented generation (RAG) is a paradigm that couples a gene…
AI Alignment & Safety: Research Digest
10 papers
Literature digest: AI alignment and safety AI alignment and safety has emerged as a central pillar of trustworthy AI, co…
RLHF: Research Digest
10 papers
Literature Digest: Reinforcement Learning from Human Feedback (RLHF) Reinforcement Learning from Human Feedback (RLHF) h…
Multimodal Foundation Models: Research Digest
10 papers
Literature digest: Multimodal foundation models Multimodal foundation models (MFMs) are large-scale models trained on di…
Mechanistic Interpretability: Research Digest
10 papers
Literature digest: Mechanistic interpretability in neural networks Mechanistic interpretability aims to reverse‑engineer…