Search Results for author:
Found 11 papers, 9 papers with code
ToXCL: A Unified Framework for Toxic Speech Detection and Explanation
This draws a unique need for unified frameworks that can effectively detect and explain implicit toxic speech.
Accelerating Greedy Coordinate Gradient and General Prompt Optimization via Probe Sampling
Safety of Large Language Models (LLMs) has become a critical issue given their rapid progresses.
Do LLMs Work on Charts? Designing Few-Shot Prompts for Chart Question Answering and Summarization
However, their application to chart-related tasks is not trivial as these tasks typically involve considering not only the underlying data but also the visual features in the chart image.
Prompt Optimization via Adversarial In-Context Learning
We propose a new method, Adversarial In-Context Learning (adv-ICL), to optimize prompt for in-context learning (ICL) by employing one LLM as a generator, another as a discriminator, and a third as a prompt modifier.
ChatGPT as a Math Questioner? Evaluating ChatGPT on Generating Pre-university Math Questions
In the context-unaware setting, we evaluate ChatGPT in generating math questions for each lesson from pre-university math curriculums that we crawl.
UniChart: A Universal Vision-language Pretrained Model for Chart Comprehension and Reasoning
Charts are very popular for analyzing data, visualizing key insights and answering complex reasoning questions about data.
Ranked #18 on
Chart Question Answering
on ChartQA
(using extra training data)
Modeling What-to-ask and How-to-ask for Answer-unaware Conversational Question Generation
In addition, we propose Conv-Distinct, a novel evaluation metric for CQG, to evaluate the diversity of the generated conversation from a context.
Retrieving Multimodal Information for Augmented Generation: A Survey
As Large Language Models (LLMs) become popular, there emerged an important trend of using multimodality to augment the LLMs' generation ability, which enables LLMs to better interact with the world.
xCodeEval: A Large Scale Multilingual Multitask Benchmark for Code Understanding, Generation, Translation and Retrieval
Recently, pre-trained large language models (LLMs) have shown impressive abilities in generating codes from natural language descriptions, repairing buggy codes, translating codes between languages, and retrieving relevant code segments.
OpenCQA: Open-ended Question Answering with Charts
In the first setting, a chart and the accompanying article is provided as input to the model.
CoHS-CQG: Context and History Selection for Conversational Question Generation
While previous studies mainly focus on how to model the flow and alignment of the conversation, there has been no thorough study to date on which parts of the context and history are necessary for the model.
