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November 20, 20254 min readA new evaluation pipeline called FiSCo uncovers hidden biases and offers an assessment framework that evolves alongside language models.
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September 2, 20253 min read
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Featured news
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CHI 20242024The potential of Generative AI, especially Large Language Models (LLMs), to transform software development is remarkable. In this paper, we focus on one area in software development called “code migration”. We define code migration as the process of transitioning the language version of a code repository by converting both the source code and its dependencies. Carefully designing an effective human-AI partnership
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2024Analytic data systems typically use data layouts to improve the performance of scanning and filtering data. Common data layout techniques include single-column sort keys, compound sort keys, and more complex multidimensional data layouts such as the Z-order. An appropriately-selected data layout over a table, in combination with metadata such as zone maps, enables the system to skip irrele-vant data blocks
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2024In contemporary machine learning approaches to bilingual lexicon induction (BLI), a model learns a mapping between the embedding spaces of a language pair. Recently, the retrieve-and-rank approach to BLI has achieved state-of-the-art results on the task. However, the problem remains challenging in low-resource settings, due to the paucity of data. The task is complicated by factors such as lexical variation
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2024Large language models (LLMs) tend to inadequately integrate input context during text generation, relying excessively on encoded prior knowledge in model parameters, potentially resulting in generated text with factual inconsistencies or contextually unfaithful content. LLMs utilize two primary knowledge sources: 1) prior (parametric) knowledge from pretraining, and 2) contextual (non-parametric) knowledge
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2024Dictionary example sentences play an important role in illustrating word definitions and usage, but manually creating quality sentences is challenging. Prior works have demonstrated that language models can be trained to generate example sentences. However, they relied on costly customized models and word sense datasets for generation and evaluation of their work. Rapid advancements in foundational models
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