SOTAVerified

Sentence Completion

Papers

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Showing 51–91 of 91 papers

TitleStatusHype
Finetuned Language Models Are Zero-Shot LearnersCode3
Differentially Private n-gram Extraction—0
Solving ESL Sentence Completion Questions via Pre-trained Neural Language ModelsCode0
Clause Final Verb Prediction in Hindi: Evidence for Noisy Channel Model of Communication—0
HONEST: Measuring Hurtful Sentence Completion in Language ModelsCode1
UNICORN on RAINBOW: A Universal Commonsense Reasoning Model on a New Multitask BenchmarkCode1
Muppet: Massive Multi-task Representations with Pre-FinetuningCode0
Learning Better Sentence Representation with Syntax Information—0
On-Device detection of sentence completion for voice assistants with low-memory footprint—0
A Mathematical Exploration of Why Language Models Help Solve Downstream Tasks—0
Defining and Evaluating Fair Natural Language Generation—0
DeBERTa: Decoding-enhanced BERT with Disentangled AttentionCode2
Language Models are Few-Shot LearnersCode3
GePpeTto Carves Italian into a Language ModelCode1
iCap: Interactive Image Captioning with Predictive Text—0
Filling Conversation Ellipsis for Better Social Dialog Understanding—0
Towards Generalizable Neuro-Symbolic Systems for Commonsense Question Answering—0
Improving Word Representations: A Sub-sampled Unigram Distribution for Negative Sampling—0
RoBERTa: A Robustly Optimized BERT Pretraining ApproachCode1
CODAH: An Adversarially-Authored Question Answering Dataset for Common SenseCode0
Second-order contexts from lexical substitutes for few-shot learning of word representations—0
HellaSwag: Can a Machine Really Finish Your Sentence?Code0
CODAH: An Adversarially Authored Question-Answer Dataset for Common SenseCode0
Probabilistic Clustering Using Maximal Matrix Norm Couplings—0
Hybrid Model For Word Prediction Using Naive Bayes and Latent Information—0
Personalized word representations Carrying Personalized Semantics Learned from Social Network Posts—0
Expect the unexpected: Harnessing Sentence Completion for Sarcasm Detection—0
Exploiting Linguistic Features for Sentence Completion—0
Learning Semantically and Additively Compositional Distributional RepresentationsCode0
Contextual LSTM (CLSTM) models for Large scale NLP tasks—0
Recurrent Memory Networks for Language ModelingCode0
A Deep Architecture for Semantic Matching with Multiple Positional Sentence RepresentationsCode0
Top-down Tree Long Short-Term Memory NetworksCode0
Dependency Recurrent Neural Language Models for Sentence CompletionCode0
Supervised Fine Tuning for Word Embedding with Integrated Knowledge—0
Learning Word Representations with Hierarchical Sparse Coding—0
Refinements to Interactive Translation Prediction Based on Search Graphs—0
Dependency Language Models for Sentence Completion—0
Regularization and nonlinearities for neural language models: when are they needed?—0
Improving Sentence Completion in Dialogues with Multi-Modal Features—0
Computational Approaches to Sentence Completion—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CompassMTL 567M with TailorAccuracy96.1—Unverified
2CompassMTL 567MAccuracy95.6—Unverified
3DeBERTa-Large 304M (classification-based)Accuracy95.6—Unverified
4GPT-4 (10-shot)Accuracy95.3—Unverified
5LLaMA3+MoSLoRAAccuracy95—Unverified
6LLaMA-2 13B + MixLoRAAccuracy94.7—Unverified
7DeBERTa-Large 304MAccuracy94.7—Unverified
8Unicorn 11B (fine-tuned)Accuracy93.9—Unverified
9LLaMA-3 8B + MixLoRAAccuracy93.3—Unverified
10LLaMA-2 7B + MixLoRAAccuracy93.1—Unverified