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Found 14 papers, 4 papers with code
Standardizing the Measurement of Text Diversity: A Tool and a Comparative Analysis of Scores
The applicability of scores extends beyond analysis of generative models; for example, we highlight applications on instruction-tuning datasets and human-produced texts.
How Much Annotation is Needed to Compare Summarization Models?
Modern instruction-tuned models have become highly capable in text generation tasks such as summarization, and are expected to be released at a steady pace.
Chain of Logic: Rule-Based Reasoning with Large Language Models
We introduce a new prompting method, Chain of Logic, which elicits rule-based reasoning through decomposition (solving elements as independent threads of logic), and recomposition (recombining these sub-answers to resolve the underlying logical expression).
Self-Debiasing Large Language Models: Zero-Shot Recognition and Reduction of Stereotypes
Large language models (LLMs) have shown remarkable advances in language generation and understanding but are also prone to exhibiting harmful social biases.
AutoDAN: Interpretable Gradient-Based Adversarial Attacks on Large Language Models
Safety alignment of Large Language Models (LLMs) can be compromised with manual jailbreak attacks and (automatic) adversarial attacks.
PDFTriage: Question Answering over Long, Structured Documents
Representing such structured documents as plain text is incongruous with the user's mental model of these documents with rich structure.
Bias and Fairness in Large Language Models: A Survey
Rapid advancements of large language models (LLMs) have enabled the processing, understanding, and generation of human-like text, with increasing integration into systems that touch our social sphere.
Evaluation Examples are not Equally Informative: How should that change NLP Leaderboards?
While leaderboards are a straightforward ranking of NLP models, this simplicity can mask nuances in evaluation items (examples) and subjects (NLP models).
Syntopical Graphs for Computational Argumentation Tasks
Approaches to computational argumentation tasks such as stance detection and aspect detection have largely focused on the text of independent claims, losing out on potentially valuable context provided by the rest of the collection.
A Joint Model for Document Segmentation and Segment Labeling
Text segmentation aims to uncover latent structure by dividing text from a document into coherent sections.
It Takes Two to Lie: One to Lie, and One to Listen
Trust is implicit in many online text conversations{---}striking up new friendships, or asking for tech support.
MATERIALizing Cross-Language Information Retrieval: A Snapshot
At about the midpoint of the IARPA MATERIAL program in October 2019, an evaluation was conducted on systems{'} abilities to find Lithuanian documents based on English queries.
Mitigating Noisy Inputs for Question Answering
We investigate and mitigate the effects of noise from Automatic Speech Recognition systems on two factoid Question Answering (QA) tasks.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+6
UMDeep at SemEval-2017 Task 1: End-to-End Shared Weight LSTM Model for Semantic Textual Similarity
After optimizing hyperparameters, we train the network on the multilingual semantic similarity task using pre-translated sentences.
