Papers
Do LLMs Agree with Humans on Emotional Associations to Nonsense Words?
Yui Miyakawa, Chihaya Matsuhira, Hirotaka Kato et al.
Do LLMs Recognize me, When I is not me: Assessment of LLMs Understanding of Turkish Indexical Pronouns in Indexical Shift Contexts
Metehan Oğuz, Yusuf Ciftci, Yavuz Faruk Bakman
Do LLMs Speak Kazakh? A Pilot Evaluation of Seven Models
Akylbek Maxutov, Ayan Myrzakhmet, Pavel Braslavski
Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research
Luca Soldaini, Rodney Kinney, Akshita Bhagia et al.
Dolomites@#SMM4H 2024: Helping LLMs “Know The Drill” in Low-Resource Settings - A Study on Social Media Posts
Giuliano Tortoreto, Seyed Mahed Mousavi
DolphCoder: Echo-Locating Code Large Language Models with Diverse and Multi-Objective Instruction Tuning
Yejie Wang, Keqing He, Guanting Dong et al.
Do LVLMs Understand Charts? Analyzing and Correcting Factual Errors in Chart Captioning
Kung-Hsiang Huang, Mingyang Zhou, Hou Pong Chan et al.
Domain Adaptation for Subjective Induction Questions Answering on Products by Adversarial Disentangled Learning
Yufeng Zhang, Jianxing Yu, Yanghui Rao et al.
Domain-Aware k-Nearest-Neighbor Knowledge Distillation for Machine Translation
Zhexuan Wang, Shudong Liu, Xuebo Liu et al.
Domain-specific or Uncertainty-aware models: Does it really make a difference for biomedical text classification?
Aman Sinha, Timothee Mickus, Marianne Clausel et al.
Do Multilingual Large Language Models Mitigate Stereotype Bias?
Shangrui Nie, Michael Fromm, Charles Welch et al.
Don’t Augment, Rewrite? Assessing Abusive Language Detection with Synthetic Data
Camilla Casula, Elisa Leonardelli, Sara Tonelli
Don’t Buy it! Reassessing the Ad Understanding Abilities of Contrastive Multimodal Models
Anna Bavaresco, Alberto Testoni, Raquel Fernández
Don’t forget private retrieval: distributed private similarity search for large language models
Guy Zyskind, Tobin South, Alex Pentland
Don’t Go To Extremes: Revealing the Excessive Sensitivity and Calibration Limitations of LLMs in Implicit Hate Speech Detection
Min Zhang, Jianfeng He, Taoran Ji et al.
Don’t Hallucinate, Abstain: Identifying LLM Knowledge Gaps via Multi-LLM Collaboration
Shangbin Feng, Weijia Shi, Yike Wang et al.
Don’t Rank, Combine! Combining Machine Translation Hypotheses Using Quality Estimation
Giorgos Vernikos, Andrei Popescu-Belis
Do Numbers Matter? Types and Prevalence of Numbers in Clinical Texts
Rahmad Mahendra, Damiano Spina, Lawrence Cavedon et al.
Do PLMs and Annotators Share the Same Gender Bias? Definition, Dataset, and Framework of Contextualized Gender Bias
Shucheng Zhu, Bingjie Du, Jishun Zhao et al.
Do Pre-Trained Language Models Detect and Understand Semantic Underspecification? Ask the DUST!
Frank Wildenburg, Michael Hanna, Sandro Pezzelle
DoRA: Enhancing Parameter-Efficient Fine-Tuning with Dynamic Rank Distribution
Yulong Mao, Kaiyu Huang, Changhao Guan et al.
DORY: Deliberative Prompt Recovery for LLM
Lirong Gao, Ru Peng, Yiming Zhang et al.
Do Zombies Understand? A Choose-Your-Own-Adventure Exploration of Machine Cognition
Ariel Goldstein, Gabriel Stanovsky
DPDLLM: A Black-box Framework for Detecting Pre-training Data from Large Language Models
Baohang Zhou, Zezhong Wang, Lingzhi Wang et al.