Ecomgpt: Instruction-tuning large language models with chain-of-task tasks for e-commerce
Recently, instruction-following Large Language Models (LLMs), represented by ChatGPT,
have exhibited exceptional performance in general Natural Language Processing (NLP) …
have exhibited exceptional performance in general Natural Language Processing (NLP) …
Mrrl: Modifying the reference via reinforcement learning for non-autoregressive joint multiple intent detection and slot filling
With the rise of non-autoregressive approach, some non-autoregressive models for joint
multiple intent detection and slot filling have obtained the promising inference speed …
multiple intent detection and slot filling have obtained the promising inference speed …
Seqgpt: An out-of-the-box large language model for open domain sequence understanding
Large language models (LLMs) have shown impressive abilities for open-domain NLP
tasks. However, LLMs are sometimes too footloose for natural language understanding …
tasks. However, LLMs are sometimes too footloose for natural language understanding …
MESED: A multi-modal entity set expansion dataset with fine-grained semantic classes and hard negative entities
The Entity Set Expansion (ESE) task aims to expand a handful of seed entities with new
entities belonging to the same semantic class. Conventional ESE methods are based on …
entities belonging to the same semantic class. Conventional ESE methods are based on …
Lateval: An interactive llms evaluation benchmark with incomplete information from lateral thinking puzzles
With the continuous evolution and refinement of LLMs, they are endowed with impressive
logical reasoning or vertical thinking capabilities. But can they think out of the box? Do they …
logical reasoning or vertical thinking capabilities. But can they think out of the box? Do they …
CLEME: debiasing multi-reference evaluation for grammatical error correction
Evaluating the performance of Grammatical Error Correction (GEC) systems is a challenging
task due to its subjectivity. Designing an evaluation metric that is as objective as possible is …
task due to its subjectivity. Designing an evaluation metric that is as objective as possible is …
When llms meet cunning questions: A fallacy understanding benchmark for large language models
Recently, Large Language Models (LLMs) have made remarkable evolutions in language
understanding and generation. Following this, various benchmarks for measuring all kinds …
understanding and generation. Following this, various benchmarks for measuring all kinds …
Towards real-world writing assistance: A chinese character checking benchmark with faked and misspelled characters
Writing assistance is an application closely related to human life and is also a fundamental
Natural Language Processing (NLP) research field. Its aim is to improve the correctness and …
Natural Language Processing (NLP) research field. Its aim is to improve the correctness and …
A Frustratingly Easy Plug-and-Play Detection-and-Reasoning Module for Chinese Spelling Check
In recent years, Chinese Spelling Check (CSC) has been greatly improved by designing
task-specific pre-training methods or introducing auxiliary tasks, which mostly solve this task …
task-specific pre-training methods or introducing auxiliary tasks, which mostly solve this task …
Mixedit: Revisiting data augmentation and beyond for grammatical error correction
Data Augmentation through generating pseudo data has been proven effective in mitigating
the challenge of data scarcity in the field of Grammatical Error Correction (GEC). Various …
the challenge of data scarcity in the field of Grammatical Error Correction (GEC). Various …