We will need you to submit all your code as a final deliverable. PLAGIARISM will be strictly penalized, see here for more details.

Project Pitch (5%)

Every student pitches a 5-minute project idea for which all the other students vote. This will help the students choose project teams. The pitch should outline the problem being solved and why should we care about it. There should be a clear connection to language models as a path to addressing the problem (i.e., it must involve language of some kind). It should also provide an idea of what the inputs and the outputs are, ideally with real-world examples. It is important to name the project idea for ease of voting.

Project Team Formation

Projects are to be done in teams of 2. Based on enrollment, we will make some exceptions if people are left behind.

Project proposal (5%).

Student teams should submit a ~1-page proposal (using the *CL paper submission template) for their project by Week 5. The proposal should:

• state and motivate the problem by providing a problem or task definition (preferably with example inputs and expected outputs),
• situate the problem within related work (this might help you find sources of data for training a model for your task),
  • Related work: publications, start by looking in the ACL anthology
  • References do not count towards page limit, but please follow the correct format
• state a hypothesis to be verified and how to verify it (evaluation framework), and
• provide a brief description of the approach to be followed to verify the hypothesis (such as proposed models and baselines).

We highly encourage students to work towards a problem involving predictive models, hence it’s worth thinking about the five key ingredients of supervised learning: data, model, loss function, optimization algorithm and inference / evaluation.

Project progress report (10%).

TBD

Project final presentation (10%).

TBD

Project final report (10%).

TBD