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Found 4 papers, 4 papers with code
ChainLM: Empowering Large Language Models with Improved Chain-of-Thought Prompting
In response to this challenge, we present an empirical investigation of CoT prompting and introduce CoTGenius, a novel framework designed for the automatic generation of superior CoT prompts.
The Dawn After the Dark: An Empirical Study on Factuality Hallucination in Large Language Models
To tackle the LLM hallucination, three key questions should be well studied: how to detect hallucinations (detection), why do LLMs hallucinate (source), and what can be done to mitigate them (mitigation).
HaluEval: A Large-Scale Hallucination Evaluation Benchmark for Large Language Models
Large language models (LLMs), such as ChatGPT, are prone to generate hallucinations, i. e., content that conflicts with the source or cannot be verified by the factual knowledge.
TextBox 2.0: A Text Generation Library with Pre-trained Language Models
To facilitate research on text generation, this paper presents a comprehensive and unified library, TextBox 2. 0, focusing on the use of pre-trained language models (PLMs).
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