ARC
104 papers with code • 0 benchmarks • 0 datasets
Benchmarks
These leaderboards are used to track progress in ARC
Most implemented papers
Finetuned Language Models Are Zero-Shot Learners
google-research/flan
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ICLR 2022
We show that instruction tuning -- finetuning language models on a collection of tasks described via instructions -- substantially improves zero-shot performance on unseen tasks.
On the Measure of Intelligence
To make deliberate progress towards more intelligent and more human-like artificial systems, we need to be following an appropriate feedback signal: we need to be able to define and evaluate intelligence in a way that enables comparisons between two systems, as well as comparisons with humans.
Learning to Attend On Essential Terms: An Enhanced Retriever-Reader Model for Open-domain Question Answering
nijianmo/arc-etrr-code
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NAACL 2019
In this paper we propose a retriever-reader model that learns to attend on essential terms during the question answering process.
Arc-support Line Segments Revisited: An Efficient and High-quality Ellipse Detection
Over the years many ellipse detection algorithms spring up and are studied broadly, while the critical issue of detecting ellipses accurately and efficiently in real-world images remains a challenge.
ST-MoE: Designing Stable and Transferable Sparse Expert Models
tensorflow/mesh
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But advancing the state-of-the-art across a broad set of natural language tasks has been hindered by training instabilities and uncertain quality during fine-tuning.
Self-Consistency Improves Chain of Thought Reasoning in Language Models
Chain-of-thought prompting combined with pre-trained large language models has achieved encouraging results on complex reasoning tasks.
FactGraph: Evaluating Factuality in Summarization with Semantic Graph Representations
amazon-research/fact-graph
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NAACL 2022
Despite recent improvements in abstractive summarization, most current approaches generate summaries that are not factually consistent with the source document, severely restricting their trust and usage in real-world applications.
Yara Parser: A Fast and Accurate Dependency Parser
At its fastest, Yara can parse about 4000 sentences per second when in greedy mode (1 beam).
More About Covariance Descriptors for Image Set Coding: Log-Euclidean Framework based Kernel Matrix Representation
We consider a family of structural descriptors for visual data, namely covariance descriptors (CovDs) that lie on a non-linear symmetric positive definite (SPD) manifold, a special type of Riemannian manifolds.
FreeLB: Enhanced Adversarial Training for Natural Language Understanding
zhuchen03/FreeLB
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ICLR 2020
Adversarial training, which minimizes the maximal risk for label-preserving input perturbations, has proved to be effective for improving the generalization of language models.
