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Found 17 papers, 7 papers with code
MixSumm: Topic-based Data Augmentation using LLMs for Low-resource Extractive Text Summarization
Low-resource extractive text summarization is a vital but heavily underexplored area of research.
InsightBench: Evaluating Business Analytics Agents Through Multi-Step Insight Generation
Second, unlike existing benchmarks focusing on answering single queries, InsightBench evaluates agents based on their ability to perform end-to-end data analytics, including formulating questions, interpreting answers, and generating a summary of insights and actionable steps.
LLM aided semi-supervision for Extractive Dialog Summarization
Generating high-quality summaries for chat dialogs often requires large labeled datasets.
Prompt-based Pseudo-labeling Strategy for Sample-Efficient Semi-Supervised Extractive Summarization
While SSL is popular for image and text classification, it is relatively underexplored for the task of extractive text summarization.
PromptMix: A Class Boundary Augmentation Method for Large Language Model Distillation
Our specific PromptMix method consists of two steps: 1) generate challenging text augmentations near class boundaries; however, generating borderline examples increases the risk of false positives in the dataset, so we 2) relabel the text augmentations using a prompting-based LLM classifier to enhance the correctness of labels in the generated data.
Multi-Modal Discussion Transformer: Integrating Text, Images and Graph Transformers to Detect Hate Speech on Social Media
We present the Multi-Modal Discussion Transformer (mDT), a novel methodfor detecting hate speech in online social networks such as Reddit discussions.
Future Sight: Dynamic Story Generation with Large Pretrained Language Models
In this work, we propose Future Sight, a method for finetuning a pretrained generative transformer on the task of future conditioning.
LyricJam Sonic: A Generative System for Real-Time Composition and Musical Improvisation
Subsequently, it is difficult for artists to rediscover audio segments that might be suitable for use in their compositions from thousands of hours of recordings.
Data Augmentation for Intent Classification with Off-the-shelf Large Language Models
Data augmentation is a widely employed technique to alleviate the problem of data scarcity.
Personalized multi-faceted trust modeling to determine trust links in social media and its potential for misinformation management
In this paper, we present an approach for predicting trust links between peers in social media, one that is grounded in the artificial intelligence area of multiagent trust modeling.
LyricJam: A system for generating lyrics for live instrumental music
We describe a real-time system that receives a live audio stream from a jam session and generates lyric lines that are congruent with the live music being played.
Towards A Multi-agent System for Online Hate Speech Detection
This paper envisions a multi-agent system for detecting the presence of hate speech in online social media platforms such as Twitter and Facebook.
Generation of lyrics lines conditioned on music audio clips
We present a system for generating novel lyrics lines conditioned on music audio.
Adversarial Learning on the Latent Space for Diverse Dialog Generation
Generating relevant responses in a dialog is challenging, and requires not only proper modeling of context in the conversation but also being able to generate fluent sentences during inference.
Adaptive Fusion Techniques for Multimodal Data
Effective fusion of data from multiple modalities, such as video, speech, and text, is challenging due to the heterogeneous nature of multimodal data.
Multimodal Speech Emotion Recognition and Ambiguity Resolution
In this work, we adopt a feature-engineering based approach to tackle the task of speech emotion recognition.
Free as in Free Word Order: An Energy Based Model for Word Segmentation and Morphological Tagging in Sanskrit
The configurational information in sentences of a free word order language such as Sanskrit is of limited use.
