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A collection of Claude Code skills for academic research workflows, including literature reviews, PhD proposals, and fidelity-first academic slides with vector equations and citations.
Introduces GRASP, a framework that combines LLM planning with graph algorithms to generate high-fidelity related work sections by modeling inter-paper relationships through a two-layer graph structure and Steiner tree pruning.
Feynman is an open-source AI research agent that automates deep arXiv searches, literature review generation, code reproduction, and more. It runs locally, reducing redundant work for researchers.
Claude Science is a tool for early-stage research that automatically retrieves, deduplicates, clusters literature and generates research maps and trend reports, which is very helpful for exploring new fields.
The tweet claims that Claude has a secret 'Research Accelerator' mode using 13 prompts to quickly process research papers into various outputs.
OpenDraft is an open-source tool that uses 19 specialized AI agents in parallel to assist with research paper writing and literature reviews, described as 'Claude Code for research papers'.
This paper evaluates the use of small language models (SLMs) to assist title and abstract screening in systematic reviews of social-physical human-robot interaction (spHRI). While SLMs did not match human performance, they operated locally at high speed and identified additional relevant papers, demonstrating their potential to augment human reviewers for large-scale literature reviews.
This paper reviews the progress in AI for Systems Engineering (AI4SE) and Systems Engineering for AI (SE4AI) over the past decade, identifies five critical research gaps, and provides a human-AI agreement dataset and web explorer for relevance judgments.
A literature review examining LLM-based approaches for automatic scoring of Arabic text, covering short answer grading and essay scoring, with a proposed taxonomy and comparative analysis.
The author introduces Sisyphus Academica, an open-source research companion that evolved from an AI-assisted writing tool into a full research workflow manager, and seeks community feedback on features and development direction.
A tweet sharing AutoSci, a system from Peking University that automates the entire research lifecycle from literature review to rebuttal, with self-improvement between projects.
The open-source AI agent Feynman, through the collaboration of four intelligent agents, compresses PhD-level research processes (including arXiv research, literature review, code verification) into fully automated execution, requiring only a single instruction from the user.
This literature review identifies and analyzes the problem of silent failures in physical AI systems, where black-box models may execute harmful actions without detection. It proposes a taxonomy of runtime guardrail functions and outlines evaluation requirements for safe autonomous systems.
Released a set of 6 Claude prompts that can quickly transform over 40 research papers into structured literature reviews, knowledge graphs, and research gap analyses, boosting research efficiency.
Google DeepMind announces Gemini for Science, a suite of experimental AI tools to help scientists explore hypotheses, validate work, and unpack literature.
Recommends the open-source repository academic-research-skills, which provides a set of human-AI collaborative tools for the entire academic research workflow, including in-depth literature research, paper writing, peer review simulation, and citation audit. It supports AI assistance while keeping the user in control, suitable for graduate students and researchers.
This article introduces a 6-step workflow for academic research using Kimi (an AI tool with a 1 million token context window), including literature dumping, gap identification, literature review draft, methodology stress testing, argument stress testing, and full-text assembly, which can significantly shorten paper writing time.
The author introduces Papira, a beta tool that analyzes uploaded research papers to map coverage and identify gaps in machine learning and NLP subfields.
Deepmind's upgraded Gemini Deep Research dramatically accelerates scientific literature review, autonomously synthesizing multi-modal data and reshaping workflows in finance, biotech, and consulting.