Can Instruction Fine-Tuned Language Models Identify Social Bias through Prompting?. (arXiv:2307.10472v1 [cs.CL])
Improving Pre-trained Language Models' Generalization. (arXiv:2307.10457v1 [cs.CL])
Integrating a Heterogeneous Graph with Entity-aware Self-attention using Relative Position Labels for Reading Comprehension Model. (arXiv:2307.10443v1 [cs.CL])
Thrust: Adaptively Propels Large Language Models with External Knowledge. (arXiv:2307.10442v1 [cs.CL])
PharmacyGPT: The AI Pharmacist. (arXiv:2307.10432v1 [cs.CL])
IncDSI: Incrementally Updatable Document Retrieval. (arXiv:2307.10323v1 [cs.IR])
Mood Classification of Bangla Songs Based on Lyrics. (arXiv:2307.10314v1 [cs.IR])
Analyzing sports commentary in order to automatically recognize events and extract insights. (arXiv:2307.10303v1 [cs.CL])
The Language Labyrinth: Constructive Critique on the Terminology Used in the AI Discourse. (arXiv:2307.10292v1 [cs.CY])
Mutual Reinforcement Effects in Japanese Sentence Classification and Named Entity Recognition Tasks. (arXiv:2307.10291v1 [cs.CL])
Zero-shot Domain-sensitive Speech Recognition with Prompt-conditioning Fine-tuning. (arXiv:2307.10274v1 [eess.AS])
Automated Action Model Acquisition from Narrative Texts. (arXiv:2307.10247v1 [cs.CL])
Deep Neural Networks and Brain Alignment: Brain Encoding and Decoding (Survey). (arXiv:2307.10246v1 [q-bio.NC])
Look Before You Leap: An Exploratory Study of Uncertainty Measurement for Large Language Models. (arXiv:2307.10236v1 [cs.SE])
SentimentGPT: Exploiting GPT for Advanced Sentiment Analysis and its Departure from Current Machine Learning. (arXiv:2307.10234v1 [cs.CL])
Mitigating Bias in Conversations: A Hate Speech Classifier and Debiaser with Prompts. (arXiv:2307.10213v1 [cs.CL])
Unsupervised Domain Adaptation using Lexical Transformations and Label Injection for Twitter Data. (arXiv:2307.10210v1 [cs.CL])
Disentangling Societal Inequality from Model Biases: Gender Inequality in Divorce Court Proceedings. (arXiv:2307.10200v1 [cs.CY])
ChatGPT for Digital Forensic Investigation: The Good, The Bad, and The Unknown. (arXiv:2307.10195v1 [cs.CR])
Subjective Crowd Disagreements for Subjective Data: Uncovering Meaningful CrowdOpinion with Population-level Learning. (arXiv:2307.10189v1 [cs.IR])
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