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Thank You for Joining Connect 2025!
We loved having researchers, builders, and collaborators from around the world come together to explore multilingual AI, open science, and collaborative innovation.
This page is your hub for session recordings, slides, key takeaways, and resources — everything you need to revisit the ideas, connect with speakers, and keep the conversation going.
Ready to start your own collaboration? Check out these resources
Ready to start your own collaboration? Check out these resources
Learn more about our Open Science Community and join us on Discord — This is the perfect place to help you start your research collaboration
Check out the #no-bad-ideas channel, the perfect place to brainstorm, share wild ideas, get feedback, and spark creative collaboration with the community!
Check out the #find-collaborators channel, this is a great space to post once you have a project scope and you are ready to get people to join you with your idea!
Learn more about the Cohere Labs Catalyst Grants which provide researchers and developers with free access to the Cohere API to support their projects and research into advancing safe, responsible LLM capabilities and applications.
You'll find posts like this one from Yiyuan who is looking for collaborators around studying the annotation problem in process rewards of reasoning problems in LLMs.
Also posts like this one from Aayan who was working on Enhancing Multilingual Language Models with Group Relative Policy Optimisation and was looking for collaborators to join their project!
Other tips and resources
Other tips and resources
Project Scope
Copy this document to help scope out your project.
Ask prospective team-members to start contributing, and track changes -- this can give you good signal for you wants to be involved.
Team Meetings
Once you have a group of collaborators, we strongly recommend setting a weekly meeting with your team to ensure you are on track and plan for the week ahead
use https://rallly.co/ or https://www.when2meet.com/ to check availability with all team members
set a recurring meeting - same time each week to avoid the operational overhead of scheduling each week
invite all team members with a calendar link so it adds to their personal calendars
Day 1
Day 1
Recording
Recording
Speakers
Speakers
Joelle Pineau
Chief AI Officer, Cohere
Marzieh Fadaee Head of Cohere Labs
Beyza Ermis
Research Scientist, Cohere Labs
Freddie Vargus
Co-founder & CTO, Quotient AI
Karthik Kanjula
Cohere Labs Community Researcher
Nahid Alam
Staff Machine Learning Engineer, Cisco Meraki
Shivalika Singh
Research Engineer, Cohere Labs
Surya Guthikonda
AI Product
Engineering Intern,
Wei-Yin Ko
Member of Technical Staff, Cohere
Zheng-Xin Yong
PhD student, Brown University
Nathanaël Carraz Rakotonirina
PhD Student
Mohammed Hamdy
ML Researcher, MOTH Lab
Day 2
Day 2
Recording
Recording
Speakers
Speakers
Ivan Zhang
Co-founder, Cohere
Bronson Bakunga
ML Engineer,
MSc student
Angelika Romanou
PhD Candidate at EPFL
Harsha Nelaturu
MSc student, Universitat Des Saarlande
Kato Steven Mubiru
Co-founder, Crane AI Labs
Dheeraj Varghese
Ph.D. candidate, University of Amsterdam
Day 3
Day 3
Speakers
Speakers
Shayne Longpre
PhD @ MIT, AI researcher
Diana Abagyan
Research Scholar, Cohere Labs
Daniel D'souza
Research Engineer, Cohere Labs
Julia Kreutzer
Sr. Research Scientist, Cohere Labs
Viraat Aryabumi
Member of Technical Staff, Cohere
Shivalika Singh
Research Engineer, Cohere Labs
Yiyang (Oliver) Nan
Member of Technical Staff, Cohere
Recordings and Slides
Recordings and Slides
TL;DR from Shayne Longpre's keynote presentation: Seven lessons on collaboration in AI research.
"Last week I gave a keynote on Collaboration in AI Research at Cohere Labs Connect 2025, alongside Cohere co-founder Ivan Zhang, Head of Cohere Labs Marzieh Fadaee, and Chief AI Officer Joelle Pineau. I’m grateful for the invitation—and for the many collaborators whose work shaped this talk.
Slides: a practical roadmap for starting an interdisciplinary research collaboration. In brief:
1. Ideate clearly. Share a one-pager with potential collaborators, advisors, and critics.
2. Run a pre-mortem. Find your “reviewer #2” early and invite their critiques to sharpen direction.
3. Recruit widely. Don’t let geography or institution limit you; add complementary skills, senior advisors, and junior contributors.
4. Structure incentives. Be explicit about authorship, credit, visibility, and impact; let people own their piece.
5. Communicate early and often. Relationships may be the most durable outcome. Align early on authorship contingencies, timeline, cadence, and responsibilities.
6. Document decisions. Keep a living record of links, choices (and why), and who did what—details slip in larger teams.
7. Focus on infrastructure & visuals. Beyond relationships, open-source tools and clear figures/tables travel the farthest and longest.
Links to Canva brainstorming boards
- Efficient Multilingual Adaptation via Universal Tokenization – Diana Abagyan
- Cracking the Long Tail: Real-Time Control for Underrepresented Task – Daniel D'souza
- Déjà Vu: Taking lessons from MT to Evaluate Multilingual LLMs — Julia Kreutzer
- To Code, or Not To Code? Exploring Impact of Code in Pre-training – Viraat Aryabumi
- The Leaderboard Illusion – Shivalika Singh and Oliver Nan
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