Papers
On the Benefits of Learning to Route in Mixture-of-Experts Models
Nishanth Dikkala, Nikhil Ghosh, Raghu Meka et al.
On the Calibration of Large Language Models and Alignment
Chiwei Zhu, Benfeng Xu, Quan Wang et al.
On the Challenges of Using Black-Box APIs for Toxicity Evaluation in Research
Luiza Pozzobon, Beyza Ermis, Patrick Lewis et al.
On the Dimensionality of Sentence Embeddings
Hongwei Wang, Hongming Zhang, Dong Yu
On the effect of curriculum learning with developmental data for grammar acquisition
Mattia Opper, J. Morrison, N. Siddharth
On the Effects of Structural Modeling for Neural Semantic Parsing
Xiang Zhang, Shizhu He, Kang Liu et al.
On the Impact of Cross-Domain Data on German Language Models
Amin Dada, Aokun Chen, Cheng Peng et al.
On the Impact of Reconstruction and Context for Argument Prediction in Natural Debate
Zlata Kikteva, Alexander Trautsch, Patrick Katzer et al.
On the Potential and Limitations of Few-Shot In-Context Learning to Generate Metamorphic Specifications for Tax Preparation Software
Dananjay Srinivas, Rohan Das, Saeid Tizpaz-Niari et al.
On the Relation between Sensitivity and Accuracy in In-Context Learning
Yanda Chen, Chen Zhao, Zhou Yu et al.
On the Representational Capacity of Recurrent Neural Language Models
Franz Nowak, Anej Svete, Li Du et al.
On the Risk of Misinformation Pollution with Large Language Models
Yikang Pan, Liangming Pan, Wenhu Chen et al.
On the Transferability of Visually Grounded PCFGs
Yanpeng Zhao, Ivan Titov
On the utility of enhancing BERT syntactic bias with Token Reordering Pretraining
Yassir El Mesbahi, Atif Mahmud, Abbas Ghaddar et al.
On the Zero-Shot Generalization of Machine-Generated Text Detectors
Xiao Pu, Jingyu Zhang, Xiaochuang Han et al.
On Uncertainty Calibration and Selective Generation in Probabilistic Neural Summarization: A Benchmark Study
Polina Zablotskaia, Du Phan, Joshua Maynez et al.
On using distribution-based compositionality assessment to evaluate compositional generalisation in machine translation
Anssi Moisio, Mathias Creutz, Mikko Kurimo
Oolong: Investigating What Makes Transfer Learning Hard with Controlled Studies
Zhengxuan Wu, Alex Tamkin, Isabel Papadimitriou
OpenAsp: A Benchmark for Multi-document Open Aspect-based Summarization
Shmuel Amar, Liat Schiff, Ori Ernst et al.
Open Domain Multi-document Summarization: A Comprehensive Study of Model Brittleness under Retrieval
John Giorgi, Luca Soldaini, Bo Wang et al.
Open-ended Commonsense Reasoning with Unrestricted Answer Candidates
Chen Ling, Xuchao Zhang, Xujiang Zhao et al.
Open-Ended Instructable Embodied Agents with Memory-Augmented Large Language Models
Gabriel Sarch, Yue Wu, Michael Tarr et al.
Open Information Extraction via Chunks
Kuicai Dong, Aixin Sun, Jung-jae Kim et al.
Open-source Large Language Models are Strong Zero-shot Query Likelihood Models for Document Ranking
Shengyao Zhuang, Bing Liu, Bevan Koopman et al.
Open-world Semi-supervised Generalized Relation Discovery Aligned in a Real-world Setting
William Hogan, Jiacheng Li, Jingbo Shang