On Large Language Models' Selection Bias in Multi-Choice Questions. (arXiv:2309.03882v1 [cs.CL])
Introducing "Forecast Utterance" for Conversational Data Science. (arXiv:2309.03877v1 [cs.CL])
OpinionGPT: Modelling Explicit Biases in Instruction-Tuned LLMs. (arXiv:2309.03876v1 [cs.CL])
FLM-101B: An Open LLM and How to Train It with $100K Budget. (arXiv:2309.03852v1 [cs.CL])
Uncovering Drift in Textual Data: An Unsupervised Method for Detecting and Mitigating Drift in Machine Learning Models. (arXiv:2309.03831v1 [cs.CL])
USA: Universal Sentiment Analysis Model & Construction of Japanese Sentiment Text Classification and Part of Speech Dataset. (arXiv:2309.03787v1 [cs.CL])
Enhancing Pipeline-Based Conversational Agents with Large Language Models. (arXiv:2309.03748v1 [cs.CL])
The Daunting Dilemma with Sentence Encoders: Success on Standard Benchmarks, Failure in Capturing Basic Semantic Properties. (arXiv:2309.03747v1 [cs.CL])
Word segmentation granularity in Korean. (arXiv:2309.03713v1 [cs.CL])
Exploring an LM to generate Prolog Predicates from Mathematics Questions. (arXiv:2309.03667v1 [cs.CL])
BNS-Net: A Dual-channel Sarcasm Detection Method Considering Behavior-level and Sentence-level Conflicts. (arXiv:2309.03658v1 [cs.CL])
Evaluating ChatGPT as a Recommender System: A Rigorous Approach. (arXiv:2309.03613v1 [cs.IR])
Loquacity and Visible Emotion: ChatGPT as a Policy Advisor. (arXiv:2309.03595v1 [cs.CL])
Evaluating the Efficacy of Supervised Learning vs Large Language Models for Identifying Cognitive Distortions and Suicidal Risks in Chinese Social Media. (arXiv:2309.03564v1 [cs.CL])
All Labels Together: Low-shot Intent Detection with an Efficient Label Semantic Encoding Paradigm. (arXiv:2309.03563v1 [cs.CL])
An Anchor Learning Approach for Citation Field Learning. (arXiv:2309.03559v1 [cs.CL])
Machine Learning for Tangible Effects: Natural Language Processing for Uncovering the Illicit Massage Industry & Computer Vision for Tactile Sensing. (arXiv:2309.03470v1 [cs.CL])
XGen-7B Technical Report. (arXiv:2309.03450v1 [cs.CL])
Improving Open Information Extraction with Large Language Models: A Study on Demonstration Uncertainty. (arXiv:2309.03433v1 [cs.CL])
From Base to Conversational: Japanese Instruction Dataset and Tuning Large Language Models. (arXiv:2309.03412v1 [cs.CL])
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