Generative Large Language Model

Generative Large Language Models (LLMs) are powerful AI systems capable of generating human-quality text, enabling advancements in various applications like dialogue systems and machine translation. Current research focuses on improving efficiency (e.g., through quantization and parallel processing), addressing biases and safety concerns (including backdoor attacks), and enhancing performance in low-resource languages via techniques like fine-tuning and prompt engineering. The impact of LLMs is significant, driving progress in natural language processing and impacting diverse fields through improved automation, enhanced accessibility, and more effective information retrieval and analysis.

Papers

October 24, 2024

Watermarking Large Language Models and the Generated Content: Opportunities and Challenges
Ruisi Zhang, Farinaz Koushanfar
Language Model Technical Challenge Emerging Opportunity Generative Large Language Model Watermarking Method Agnostic Watermarking Generated Text

October 14, 2024

Use Random Selection for Now: Investigation of Few-Shot Selection Strategies in LLM-based Text Augmentation for Classification
Jan Cegin, Branislav Pecher, Jakub Simko, Ivan Srba, Maria Bielikova, Peter Brusilovsky
Classification Code General Strategy Generative Large Language Model Text Augmentation Shot Approach Shot Recognition Random Selection

October 2, 2024

Intent Detection in the Age of LLMs
Gaurav Arora, Shreya Jain, Srujana Merugu
Large Language Model Intent Detection Generative Large Language Model Task Oriented Dialogue System Speech Based Age Sentence Transformer Intent Label

September 23, 2024

CSPS: A Communication-Efficient Sequence-Parallelism based Serving System for Transformer based Models with Long Prompts
Zeyu Zhang, Haiying Shen
Transformer Based Complex Prompt Long Sequence Generative Large Language Model Sequence Parallelism

September 15, 2024

Leveraging Open-Source Large Language Models for Native Language Identification
Yee Man Ng, Ilia Markov
Open Source Large Language Model Generative Large Language Model Language Identification Closed Source Large Language Model Native Language Identification

September 12, 2024

Fine-tuning Large Language Models for Entity Matching
Aaron Steiner, Ralph Peeters, Christian Bizer
Pre Trained Language Model Generative Large Language Model Entity Matching Fine Tuned LLM LLM Explanation

September 10, 2024

Extracting Paragraphs from LLM Token Activations
Nicholas Pochinkov, Angelo Benoit, Lovkush Agarwal, Zainab Ali Majid, Lucile Ter-Minassian
Natural Language Processing Task Generative Large Language Model Token Prediction Contextual Understanding Paragraph Level

September 6, 2024

August 29, 2024

LLMs vs Established Text Augmentation Techniques for Classification: When do the Benefits Outweight the Costs?
Jan Cegin, Jakub Simko, Peter Brusilovsky
Large Language Model Classification Code LLM Based Generative Large Language Model Complementary Benefit Hidden CoST LLM Based Augmentation

August 23, 2024

BackdoorLLM: A Comprehensive Benchmark for Backdoor Attacks on Large Language Models
Yige Li, Hanxun Huang, Yunhan Zhao, Xingjun Ma, Jun Sun
Backdoor Attack Generative Large Language Model Comprehensive Benchmark

August 5, 2024

BOTS-LM: Training Large Language Models for Setswana
Nathan Brown, Vukosi Marivate
Large Language Model Language Model Generative Large Language Model African Language Bilingual Model Temporal Segmentation MT Model

August 1, 2024

In-Context Example Selection via Similarity Search Improves Low-Resource Machine Translation
Armel Zebaze, Benoît Sagot, Rachel Bawden
Machine Translation Sentence Embeddings Generative Large Language Model Context Example Similarity Search LLM Based Machine Translation

July 25, 2024

Difficulty Estimation and Simplification of French Text Using LLMs
Henri Jamet, Yash Raj Shrestha, Michalis Vlachos
Large Language Model Transfer Learning Medical LLM Generative Large Language Model Text Simplification Document Simplification Difficulty Estimation

July 23, 2024

Finetuning Generative Large Language Models with Discrimination Instructions for Knowledge Graph Completion
Yang Liu, Xiaobin Tian, Zequn Sun, Wei Hu
Large Language Model Knowledge Graph Text Generation Knowledge Graph Completion Generative Large Language Model Model Completion

July 6, 2024

AI Safety in Generative AI Large Language Models: A Survey
Jaymari Chua, Yun Li, Shiyi Yang, Chen Wang, Lina Yao
Timely Survey Generative AI Generative Language Model Generative Large Language Model AI Safety

July 3, 2024

GPTQT: Quantize Large Language Models Twice to Push the Efficiency
Yipin Guo, Yilin Lang, Qinyuan Ren
High Efficiency GPT Neo Post Training Quantization Generative Large Language Model Product Quantization Linear Quantization

July 2, 2024

Generative Large Language Models in Automated Fact-Checking: A Survey
Ivan Vykopal, Matúš Pikuliak, Simon Ostermann, Marián Šimko
Large Language Model Timely Survey Fact Checking Generative Large Language Model Automated Fact Checking

June 18, 2024

PlanRAG: A Plan-then-Retrieval Augmented Generation for Generative Large Language Models as Decision Makers
Myeonghwa Lee, Seonho An, Min-Soo Kim
Retrieval Augmented Generation Decision Making Retrieval Augmented Generative Large Language Model Decision Maker Decision Making Benchmark

June 17, 2024

Do Not Design, Learn: A Trainable Scoring Function for Uncertainty Estimation in Generative LLMs
Duygu Nur Yaldiz, Yavuz Faruk Bakman, Baturalp Buyukates, Chenyang Tao, Anil Ramakrishna, Dimitrios Dimitriadis, Jieyu Zhao, Salman Avestimehr
Uncertainty Estimation Generative Large Language Model Score Normalization

Generative Large Language Model

Papers

Watermarking Large Language Models and the Generated Content: Opportunities and Challenges

Use Random Selection for Now: Investigation of Few-Shot Selection Strategies in LLM-based Text Augmentation for Classification

Intent Detection in the Age of LLMs

CSPS: A Communication-Efficient Sequence-Parallelism based Serving System for Transformer based Models with Long Prompts

Leveraging Open-Source Large Language Models for Native Language Identification

Fine-tuning Large Language Models for Entity Matching

Extracting Paragraphs from LLM Token Activations

Learning vs Retrieval: The Role of In-Context Examples in Regression with LLMs

OPAL: Outlier-Preserved Microscaling Quantization Accelerator for Generative Large Language Models

LLMs vs Established Text Augmentation Techniques for Classification: When do the Benefits Outweight the Costs?

BackdoorLLM: A Comprehensive Benchmark for Backdoor Attacks on Large Language Models

BOTS-LM: Training Large Language Models for Setswana

In-Context Example Selection via Similarity Search Improves Low-Resource Machine Translation

Difficulty Estimation and Simplification of French Text Using LLMs

Finetuning Generative Large Language Models with Discrimination Instructions for Knowledge Graph Completion

AI Safety in Generative AI Large Language Models: A Survey

GPTQT: Quantize Large Language Models Twice to Push the Efficiency

Generative Large Language Models in Automated Fact-Checking: A Survey

PlanRAG: A Plan-then-Retrieval Augmented Generation for Generative Large Language Models as Decision Makers

Do Not Design, Learn: A Trainable Scoring Function for Uncertainty Estimation in Generative LLMs