How much do language models copy from their training data? evaluating linguistic novelty in text generation using raven
Current language models can generate high-quality text. Are they simply copying text they
have seen before, or have they learned generalizable linguistic abstractions? To tease apart …
have seen before, or have they learned generalizable linguistic abstractions? To tease apart …
Naturalprover: Grounded mathematical proof generation with language models
Theorem proving in natural mathematical language–the mixture of symbolic and natural
language used by humans–plays a central role in mathematical advances and education …
language used by humans–plays a central role in mathematical advances and education …
LM-critic: Language models for unsupervised grammatical error correction
Training a model for grammatical error correction (GEC) requires a set of labeled
ungrammatical/grammatical sentence pairs, but manually annotating such pairs can be …
ungrammatical/grammatical sentence pairs, but manually annotating such pairs can be …
A survey on evaluation of summarization methods
The increasing volume of textual information on any topic requires its compression to allow
humans to digest it. This implies detecting the most important information and condensing it …
humans to digest it. This implies detecting the most important information and condensing it …
Dtvlt: A multi-modal diverse text benchmark for visual language tracking based on llm
Visual language tracking (VLT) has emerged as a cutting-edge research area, harnessing
linguistic data to enhance algorithms with multi-modal inputs and broadening the scope of …
linguistic data to enhance algorithms with multi-modal inputs and broadening the scope of …
MedChatZH: A tuning LLM for traditional Chinese medicine consultations
Abstract Generative Large Language Models (LLMs) have achieved significant success in
various natural language processing tasks, including Question-Answering (QA) and …
various natural language processing tasks, including Question-Answering (QA) and …
Reassessing the goals of grammatical error correction: Fluency instead of grammaticality
The field of grammatical error correction (GEC) has grown substantially in recent years, with
research directed at both evaluation metrics and improved system performance against …
research directed at both evaluation metrics and improved system performance against …
Can Language Models Make Fun? A Case Study in Chinese Comical Crosstalk
Artificial Intelligence (AI) has been widely used in Natural Language Processing (NLP),
computer vision, speech, robots, and further applied biology, etc. In NLP, Pre-trained …
computer vision, speech, robots, and further applied biology, etc. In NLP, Pre-trained …
[HTML][HTML] Large Language Models, scientific knowledge and factuality: A framework to streamline human expert evaluation
Objective: The paper introduces a framework for the evaluation of the encoding of factual
scientific knowledge, designed to streamline the manual evaluation process typically …
scientific knowledge, designed to streamline the manual evaluation process typically …
Fireball: A dataset of dungeons and dragons actual-play with structured game state information
Dungeons & Dragons (D&D) is a tabletop roleplaying game with complex natural language
interactions between players and hidden state information. Recent work has shown that …
interactions between players and hidden state information. Recent work has shown that …