Search Results for author:
Found 8 papers, 6 papers with code
ChatGLM-RLHF: Practices of Aligning Large Language Models with Human Feedback
The work presents our practices of aligning LLMs with human preferences, offering insights into the challenges and solutions in RLHF implementations.
Towards Efficient and Exact Optimization of Language Model Alignment
We prove that EXO is guaranteed to optimize in the same direction as the RL algorithms asymptotically for arbitary parametrization of the policy, while enables efficient optimization by circumventing the complexities associated with RL algorithms.
A Semantic-based Method for Unsupervised Commonsense Question Answering
In this paper, we present a novel SEmantic-based Question Answering method (SEQA) for unsupervised commonsense question answering.
REPT: Bridging Language Models and Machine Reading Comprehension via Retrieval-Based Pre-training
Pre-trained Language Models (PLMs) have achieved great success on Machine Reading Comprehension (MRC) over the past few years.
A Self-Training Method for Machine Reading Comprehension with Soft Evidence Extraction
Neural models have achieved great success on machine reading comprehension (MRC), many of which typically consist of two components: an evidence extractor and an answer predictor.
CoTK: An Open-Source Toolkit for Fast Development and Fair Evaluation of Text Generation
In text generation evaluation, many practical issues, such as inconsistent experimental settings and metric implementations, are often ignored but lead to unfair evaluation and untenable conclusions.
Word Embedding based Edit Distance
Text similarity calculation is a fundamental problem in natural language processing and related fields.
Improved Word Representation Learning with Sememes
The key idea is to utilize word sememes to capture exact meanings of a word within specific contexts accurately.
