Sentence Completion
45 papers with code • 1 benchmarks • 2 datasets
Benchmarks
These leaderboards are used to track progress in Sentence Completion
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Libraries
Use these libraries to find Sentence Completion models and implementations
HellaSwag
xP3
Latest papers
The CoT Collection: Improving Zero-shot and Few-shot Learning of Language Models via Chain-of-Thought Fine-Tuning
Furthermore, we show that instruction tuning with CoT Collection allows LMs to possess stronger few-shot learning capabilities on 4 domain-specific tasks, resulting in an improvement of +2. 24% (Flan-T5 3B) and +2. 37% (Flan-T5 11B), even outperforming ChatGPT utilizing demonstrations until the max length by a +13. 98% margin.
PaLM 2 Technical Report
Through extensive evaluations on English and multilingual language, and reasoning tasks, we demonstrate that PaLM 2 has significantly improved quality on downstream tasks across different model sizes, while simultaneously exhibiting faster and more efficient inference compared to PaLM.
LaMini-LM: A Diverse Herd of Distilled Models from Large-Scale Instructions
The results demonstrate that our proposed LaMini-LM models are comparable to competitive baselines, while being much smaller in size.
GPT-4 Technical Report
We report the development of GPT-4, a large-scale, multimodal model which can accept image and text inputs and produce text outputs.
LLaMA: Open and Efficient Foundation Language Models
huggingface/transformers
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arXiv 2023
We introduce LLaMA, a collection of foundation language models ranging from 7B to 65B parameters.
Exploring the Benefits of Training Expert Language Models over Instruction Tuning
joeljang/elm
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Recently, Language Models (LMs) instruction-tuned on multiple tasks, also known as multitask-prompted fine-tuning (MT), have shown the capability to generalize to unseen tasks.
Crosslingual Generalization through Multitask Finetuning
We find finetuning large multilingual language models on English tasks with English prompts allows for task generalization to non-English languages that appear only in the pretraining corpus.
Two is Better than Many? Binary Classification as an Effective Approach to Multi-Choice Question Answering
declare-lab/team
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We show the efficacy of our proposed approach in different tasks -- abductive reasoning, commonsense question answering, science question answering, and sentence completion.
DiscoSense: Commonsense Reasoning with Discourse Connectives
We present DiscoSense, a benchmark for commonsense reasoning via understanding a wide variety of discourse connectives.
Task Compass: Scaling Multi-task Pre-training with Task Prefix
Leveraging task-aware annotated data as supervised signals to assist with self-supervised learning on large-scale unlabeled data has become a new trend in pre-training language models.
