We have 2 of 22 papers
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
A small concept generator is optimized with reinforcement learning so that its concepts maximize the downstream success of a larger, frozen answer generator, and can thus be trained into an effective, reusable search policy for a much larger one.
This work offers the first random generator of synthetic causal benchmarks with coverage guarantees and transparent assumptions operating on the three levels of causal reasoning: observation, intervention, and counterfactual, and demonstrates its utility by evaluating several state-of-the-art methods under diverse cond...
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
