PaperBench: Evaluating AI's Ability to Replicate AI Research
Cited by OpenAI
Spring Deadline: Sunday, February 15 at 11:59 pm PT. Click here to apply.

Join a rigorous research program where high school and undergraduate students work alongside world-class researchers to publish at top AI conferences.
Join a rigorous research program where high school and undergraduate students work alongside world-class researchers to publish at top AI conferences.
Choose the cohort that fits your schedule
Targeted Venues: ICML, COLM
Targeted Venues: NeurIPS, EMNLP, AAAI
Algoverse research teams have consistently achieved publication success at top AI venues such as NeurIPS, EMNLP, and ACL—conferences that primarily feature work from Ph.D. students and professional researchers at leading industry and academic labs. Acceptance rates at top conferences and workshops are typically 30-50% for submissions from established research institutions. Algoverse's research teams have significantly exceeded the baseline results, reflecting the program's emphasis on rigorous mentorship and research quality.
To read more about our research outcomes and conference publications, visit our Research page.
68%
Conference-Accepted Teams70%
Conference-Accepted Teams71%
Conference-Accepted Teams––
Results PendingUndergraduate students, high school students, and industry professionals worldwide. Python programming experience required.
$3,325 program fee includes computational resources and infrastructure for ML research. Scholarships available for qualified applicants.
We are committed to making our program accessible to all students, regardless of their financial background. To this end, we offer a limited number of financial aid scholarships. Scholarships are available to students who face significant financial hardship. Families with an annual income below $70,000 USD are given priority. Applicants need to provide a brief statement explaining their financial situation and need for support. Merit: Additionally, we offer a limited number of merit scholarships open to any interested applicants. This scholarship is highly competitive.
Phase 1
Week 1
Program orientation and high-level lectures on modern ML/LLMs and research fundamentals. Includes mentor office hours and initial readings to prepare teams for project planning.
Week 3
Team-matching completes in this window; teams choose a research topic, align on scope and success metrics, and produce a concise implementation plan to move into development.
Week 5
Finalize proposals with defined datasets, evaluation criteria, and a milestone plan. Prepare initial baseline code and data stubs.
Phase 2
Week 7
Develop working prototypes and baselines, implement evaluation pipelines, and ensure reproducible training and logging.
Week 9
Run iterative experiments and ablations, produce preliminary analyses and figures, and incorporate mentor feedback into method refinement.
Phase 3
Week 11
Submit a complete draft for internal review, address requested revisions, and ensure experiments are reproducible for handoff.
Week 13
Finalize manuscript and artifacts, submit to the chosen venue, and prepare an artifact release (code, data, README) for handoff.
Undergraduate research cited by premier institutions is already a rare and exceptional achievement—demonstrating the quality, depth, and real-world impact of our students' work. But at Algoverse, even high school students regularly earn citations from researchers at top universities and labs—a nearly unheard-of accomplishment in academia. Citations represent more than just recognition; they reflect meaningful contributions to science itself. The fact that our students' discoveries are informing research conducted by seasoned scholars underscores the extraordinary rigor, originality, and influence of their work.
Cited by OpenAI
Cited by Microsoft, Oxford, University of Washington
Cited by Princeton, MIT










Apply in one step. The application is straightforward and takes about 10 minutes. We review submissions on a rolling basis and reach out quickly if there's a fit.
We look for clear signals of technical ability (projects, coursework, competitions, or strong research curiosity), high agency and follow-through, and a genuine curiosity to do real research.
If you're ready to ship experiments and iterate fast, you'll thrive here. If admitted, you'll join a structured research pipeline with mentorship that keeps progress moving from ideation → implementation → conference submission.
