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Found 4 papers, 3 papers with code
In Search of the Long-Tail: Systematic Generation of Long-Tail Inferential Knowledge via Logical Rule Guided Search
We further use the data generated by LINK to construct a dataset Logic-Induced-Long-Tail (LINT) that can be used to evaluate downstream models on the long-tail distribution; LINT contains 108K knowledge statements spanning four domains.
Efficiently Measuring the Cognitive Ability of LLMs: An Adaptive Testing Perspective
Different tests for different models using efficient adaptive testing -- we believe this has the potential to become a new norm in evaluating large language models.
A Novel Approach for Auto-Formulation of Optimization Problems
In the Natural Language for Optimization (NL4Opt) NeurIPS 2022 competition, competitors focus on improving the accessibility and usability of optimization solvers, with the aim of subtask 1: recognizing the semantic entities that correspond to the components of the optimization problem; subtask 2: generating formulations for the optimization problem.
Towards a Holistic Understanding of Mathematical Questions with Contrastive Pre-training
To this end, in this paper, we propose a novel contrastive pre-training approach for mathematical question representations, namely QuesCo, which attempts to bring questions with more similar purposes closer.
