Câu lạc bộ Trí tuệ nhân tạo DUT

You can run end-to-end research: formulate questions, perform systematic literature searches, verify sources, synthesize evidence, assess bias, run meta-analysis, and compile APA 7.0 reports. Eight modes include quick briefs, fact-checking, three-way literature scans, and Socratic guided research dialogue.

Graduate students, academic researchers, and ML engineers. The deep-research, academic-paper, and reviewer skills target manuscript authors preparing submissions, while pytorch-lightning serves deep learning practitioners needing clean, scalable training loops with minimal boilerplate.

It chains deep-research, academic-paper, and academic-paper-reviewer into a 10-stage flow: research, write, integrity check, two-stage peer review, revision cycles, final integrity verification, and finalization, with reproducible quality gates at each stage.

It is MIT-licensed and depends on the lightning, torch, and transformers packages. It provides the Trainer class, callbacks, and automatic distributed training via DDP, FSDP, or DeepSpeed, scaling identical code from a laptop to a supercomputer.

Yes. It simulates five independent personas—an editor-in-chief, three peer reviewers, and a Devil's Advocate—with field-specific expertise. Modes include full review, re-review verification, quick assessment, methodology focus, Socratic guidance, and reviewer calibration.