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Found 16 papers, 8 papers with code
Visualizing Cross‐Lingual Discourse Relations in Multilingual TED Corpora
This paper presents an interactive data dashboard that provides users with an overview of the preservation of discourse relations among 28 language pairs.
PATQUEST: Papago Translation Quality Estimation
This paper describes the system submitted by Papago team for the quality estimation task at WMT 2020.
Anchors Aweigh! Sail for Optimal Unified Multi-Modal Representations
We theoretically demonstrate that our method captures three crucial properties of multimodal learning: intra-modal learning, inter-modal learning, and multimodal alignment, while also constructing a robust unified representation across all modalities.
Human-AI Collaborative Taxonomy Construction: A Case Study in Profession-Specific Writing Assistants
Large Language Models (LLMs) have assisted humans in several writing tasks, including text revision and story generation.
Threads of Subtlety: Detecting Machine-Generated Texts Through Discourse Motifs
With the advent of large language models (LLM), the line between human-crafted and machine-generated texts has become increasingly blurred.
Under the Surface: Tracking the Artifactuality of LLM-Generated Data
This work delves into the expanding role of large language models (LLMs) in generating artificial data.
Benchmarking Cognitive Biases in Large Language Models as Evaluators
We then evaluate the quality of ranking outputs introducing the Cognitive Bias Benchmark for LLMs as Evaluators (CoBBLEr), a benchmark to measure six different cognitive biases in LLM evaluation outputs, such as the Egocentric bias where a model prefers to rank its own outputs highly in evaluation.
An Analysis of Reader Engagement in Literary Fiction through Eye Tracking and Linguistic Features
Capturing readers' engagement in fiction is a challenging but important aspect of narrative understanding.
A Survey of Diffusion Models in Natural Language Processing
In NLP, diffusion models have been used in a variety of applications, such as natural language generation, sentiment analysis, topic modeling, and machine translation.
"Is the Pope Catholic?" Applying Chain-of-Thought Reasoning to Understanding Conversational Implicatures
Conversational implicatures are pragmatic inferences that require listeners to deduce the intended meaning conveyed by a speaker from their explicit utterances.
Improving Iterative Text Revision by Learning Where to Edit from Other Revision Tasks
Leveraging datasets from other related text editing NLP tasks, combined with the specification of editable spans, leads our system to more accurately model the process of iterative text refinement, as evidenced by empirical results and human evaluations.
Read, Revise, Repeat: A System Demonstration for Human-in-the-loop Iterative Text Revision
Examining and evaluating the capability of large language models for making continuous revisions and collaborating with human writers is a critical step towards building effective writing assistants.
Understanding Iterative Revision from Human-Written Text
Writing is, by nature, a strategic, adaptive, and more importantly, an iterative process.
Do Multilingual Neural Machine Translation Models Contain Language Pair Specific Attention Heads?
Recent studies on the analysis of the multilingual representations focus on identifying whether there is an emergence of language-independent representations, or whether a multilingual model partitions its weights among different languages.
A Multilingual Neural Machine Translation Model for Biomedical Data
We release a multilingual neural machine translation model, which can be used to translate text in the biomedical domain.
