Search Results for author: Rahul Nadkarni

Found 3 papers, 3 papers with code

Binding Language Models in Symbolic Languages

1 code implementation6 Oct 2022 Zhoujun Cheng, Tianbao Xie, Peng Shi, Chengzu Li, Rahul Nadkarni, Yushi Hu, Caiming Xiong, Dragomir Radev, Mari Ostendorf, Luke Zettlemoyer, Noah A. Smith, Tao Yu

We propose Binder, a training-free neural-symbolic framework that maps the task input to a program, which (1) allows binding a unified API of language model (LM) functionalities to a programming language (e. g., SQL, Python) to extend its grammar coverage and thus tackle more diverse questions, (2) adopts an LM as both the program parser and the underlying model called by the API during execution, and (3) requires only a few in-context exemplar annotations.

Language Modelling Semantic Parsing +1

Third-Party Language Model Performance Prediction from Instruction

1 code implementation19 Mar 2024 Rahul Nadkarni, Yizhong Wang, Noah A. Smith

Language model-based instruction-following systems have lately shown increasing performance on many benchmark tasks, demonstrating the capability of adapting to a broad variety of instructions.

Instruction Following Language Modelling

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