Search Results for author:
Found 13 papers, 7 papers with code
Incubating Text Classifiers Following User Instruction with Nothing but LLM
In this paper, we aim to generate text classification data given arbitrary class definitions (i. e., user instruction), so one can train a small text classifier without any human annotation or raw corpus.
Learn from Failure: Fine-Tuning LLMs with Trial-and-Error Data for Intuitionistic Propositional Logic Proving
Recent advances in Automated Theorem Proving have shown the effectiveness of leveraging a (large) language model that generates tactics (i. e. proof steps) to search through proof states.
MetaIE: Distilling a Meta Model from LLM for All Kinds of Information Extraction Tasks
We construct the distillation dataset via sampling sentences from language model pre-training datasets (e. g., OpenWebText in our implementation) and prompting an LLM to identify the typed spans of "important information".
Answer is All You Need: Instruction-following Text Embedding via Answering the Question
This work aims to build a text embedder that can capture characteristics of texts specified by user instructions.
Less than One-shot: Named Entity Recognition via Extremely Weak Supervision
We study the named entity recognition (NER) problem under the extremely weak supervision (XWS) setting, where only one example entity per type is given in a context-free way.
EmojiLM: Modeling the New Emoji Language
With the rapid development of the internet, online social media welcomes people with different backgrounds through its diverse content.
Generating Efficient Training Data via LLM-based Attribute Manipulation
In this paper, we propose a novel method, Chain-of-Thoughts Attribute Manipulation (CoTAM), to guide few-shot learning by carefully crafted data from Large Language Models (LLMs).
Evaluate Confidence Instead of Perplexity for Zero-shot Commonsense Reasoning
In detail, it works on PLMs according to the Replaced Token Detection (RTD) pre-training objective in ELECTRA, in which the corruption detection objective reflects the confidence on contextual integrity that is more relevant to commonsense reasoning than existing probability.
Solution of DeBERTaV3 on CommonsenseQA
We report the performance of DeBERTaV3 on CommonsenseQA in this report.
Semantics-Preserved Distortion for Personal Privacy Protection in Information Management
As the model training on information from users is likely to invade personal privacy, many methods have been proposed to block the learning and memorizing of the sensitive data in raw texts.
Unsupervised Full Constituency Parsing with Neighboring Distribution Divergence
Unsupervised constituency parsing has been explored much but is still far from being solved.
Contextualized Semantic Distance between Highly Overlapped Texts
Overlapping frequently occurs in paired texts in natural language processing tasks like text editing and semantic similarity evaluation.
Sparse Fuzzy Attention for Structured Sentiment Analysis
Attention scorers have achieved success in parsing tasks like semantic and syntactic dependency parsing.
