Towards Better Multi-modal Keyphrase Generation via Visual Entity Enhancement and Multi-granularity Image Noise Filtering. (arXiv:2309.04734v1 [cs.CV])
EPA: Easy Prompt Augmentation on Large Language Models via Multiple Sources and Multiple Targets. (arXiv:2309.04725v1 [cs.CL])
Toward Reproducing Network Research Results Using Large Language Models. (arXiv:2309.04716v1 [cs.LG])
Analysis of Disinformation and Fake News Detection Using Fine-Tuned Large Language Model. (arXiv:2309.04704v1 [cs.CL])
Code-Style In-Context Learning for Knowledge-Based Question Answering. (arXiv:2309.04695v1 [cs.CL])
Embedding structure matters: Comparing methods to adapt multilingual vocabularies to new languages. (arXiv:2309.04679v1 [cs.CL])
FIAT: Fusing learning paradigms with Instruction-Accelerated Tuning. (arXiv:2309.04663v1 [cs.CL])
MADLAD-400: A Multilingual And Document-Level Large Audited Dataset. (arXiv:2309.04662v1 [cs.CL])
Exploring Large Language Models for Communication Games: An Empirical Study on Werewolf. (arXiv:2309.04658v1 [cs.CL])
Efficient Finetuning Large Language Models For Vietnamese Chatbot. (arXiv:2309.04646v1 [cs.CL])
Can NLP Models 'Identify', 'Distinguish', and 'Justify' Questions that Don't have a Definitive Answer?. (arXiv:2309.04635v1 [cs.CL])
Linking Symptom Inventories using Semantic Textual Similarity. (arXiv:2309.04607v1 [cs.CL])
When Less is More: Investigating Data Pruning for Pretraining LLMs at Scale. (arXiv:2309.04564v1 [cs.CL])
Three Ways to Improve Verbo-visual Fusion for Dense 3D Visual Grounding. (arXiv:2309.04561v1 [cs.CV])
Retrieving Evidence from EHRs with LLMs: Possibilities and Challenges. (arXiv:2309.04550v1 [cs.CL])
Comparing How a Chatbot References User Utterances from Previous Chatting Sessions: An Investigation of Users' Privacy Concerns and Perceptions. (arXiv:2308.04879v1 [cs.HC] CROSS LISTED)
On Large Language Models' Selection Bias in Multi-Choice Questions. (arXiv:2309.03882v2 [cs.CL] UPDATED)
Exploring an LM to generate Prolog Predicates from Mathematics Questions. (arXiv:2309.03667v2 [cs.CL] UPDATED)
All Labels Together: Low-shot Intent Detection with an Efficient Label Semantic Encoding Paradigm. (arXiv:2309.03563v2 [cs.CL] UPDATED)
Large Content And Behavior Models To Understand, Simulate, And Optimize Content And Behavior. (arXiv:2309.00359v2 [cs.CL] UPDATED)
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