Search Results for author:
Found 14 papers, 7 papers with code
Enhancing Adversarial Resistance in LLMs with Recursion
The increasing integration of Large Language Models (LLMs) into society necessitates robust defenses against vulnerabilities from jailbreaking and adversarial prompts.
BordIRlines: A Dataset for Evaluating Cross-lingual Retrieval-Augmented Generation
Large language models excel at creative generation but continue to struggle with the issues of hallucination and bias.
Uncovering Differences in Persuasive Language in Russian versus English Wikipedia
We study how differences in persuasive language across Wikipedia articles, written in either English and Russian, can uncover each culture's distinct perspective on different subjects.
Eliciting Better Multilingual Structured Reasoning from LLMs through Code
xSTREET exposes a gap in base LLM performance between English and non-English reasoning tasks.
Large Language Models as Sous Chefs: Revising Recipes with GPT-3
With their remarkably improved text generation and prompting capabilities, large language models can adapt existing written information into forms that are easier to use and understand.
This Land is {Your, My} Land: Evaluating Geopolitical Biases in Language Models
We then evaluate various multilingual LLMs on our dataset and metrics to probe their internal knowledge and use the proposed metrics to discover numerous inconsistencies in how these models respond in different languages.
PAXQA: Generating Cross-lingual Question Answering Examples at Training Scale
This work proposes a synthetic data generation method for cross-lingual QA which leverages indirect supervision from existing parallel corpora.
Word Alignment in the Era of Deep Learning: A Tutorial
Jumping forward to the era of neural machine translation (NMT), we show how insights from word alignment inspired the attention mechanism fundamental to present-day NMT.
CREATIVESUMM: Shared Task on Automatic Summarization for Creative Writing
We detail the process of curating these datasets for the task, as well as the metrics used for the evaluation of the submissions.
Bidirectional Language Models Are Also Few-shot Learners
An arbitrary task can be reformulated as a natural language prompt, and a language model can be asked to generate the completion, indirectly performing the task in a paradigm known as prompt-based learning.
$\rm{C {\small IS}}^2$: A Simplified Commonsense Inference Evaluation for Story Prose
Transformers have been showing near-human performance on a variety of tasks, but they are not without their limitations.
Exploring Content Selection in Summarization of Novel Chapters
We present a new summarization task, generating summaries of novel chapters using summary/chapter pairs from online study guides.
Cantonese Automatic Speech Recognition Using Transfer Learning from Mandarin
We propose a system to develop a basic automatic speech recognizer(ASR) for Cantonese, a low-resource language, through transfer learning of Mandarin, a high-resource language.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
