Large Language Model

Large language models (LLMs) are sophisticated AI systems designed to process and generate human-like text, aiming to improve various natural language processing tasks. Current research focuses on enhancing LLM safety, efficiency (through techniques like quantization and optimized decoding), and fairness, as well as improving their ability to perform complex reasoning and handle diverse instructions. These advancements are significant because they address critical limitations in current LLMs and pave the way for broader applications across diverse fields, including healthcare, legal tech, and autonomous systems.

Papers

November 7, 2024

Bayesian Calibration of Win Rate Estimation with LLM Evaluators
Yicheng Gao, Gonghan Xu, Zhe Wang, Arman Cohan
Large Language Model Generative Language Model LLM Evaluator Probability Estimation Bayesian Calibration
Variational Low-Rank Adaptation Using IVON
Bai Cong, Nico Daheim, Yuesong Shen, Daniel Cremers, Rio Yokota, Mohammad Emtiyaz Khan, Thomas Möllenhoff
Large Language Model Adaptation Concern Large Language Variational Method Variational Learning Online Newton
Leveraging LLMs to Enable Natural Language Search on Go-to-market Platforms
Jesse Yao, Saurav Acharya, Priyaranjan Parida, Srinivas Attipalli, Ali Dasdan
Large Language Model Diverse Platform Natural Language Query Entity Retrieval
Unlearning in- vs. out-of-distribution data in LLMs under gradient-based method
Teodora Baluta, Pascal Lamblin, Daniel Tarlow, Fabian Pedregosa, Gintare Karolina Dziugaite
Large Language Model Practical Method Distribution Data Unlearning Framework Harmful Unlearning
Benchmarking Large Language Models with Integer Sequence Generation Tasks
Daniel O'Malley, Manish Bhattarai, Javier Santos
Large Language Model New Task Input Sequence Sequence Generation Novel Benchmark Code Synthesis
Measuring short-form factuality in large language models
Jason Wei, Nguyen Karina, Hyung Won Chung, Yunxin Joy Jiao, Spencer Papay, Amelia Glaese, John Schulman, William Fedus
Large Language Model Global Evaluation GPT 4 Non Negative Textual Response Factual Claim
Robust and Efficient Fine-tuning of LLMs with Bayesian Reparameterization of Low-Rank Adaptation
Vaibhav Seth, Arinjay Pathak, Ayan Sengupta, Natraj Raman, Sriram Gopalakrishnan, Tanmoy Chakraborty
Large Language Model Fine Tuning Parameter Efficient Fine Tuning Adaptation Concern Bayesian Perspective Efficient Fine Tuning Reparameterization Method
CodeTree: Agent-guided Tree Search for Code Generation with Large Language Models
Jierui Li, Hung Le, Yinbo Zhou, Caiming Xiong, Silvio Savarese, Doyen Sahoo
Large Language Model Language Model Code Generation Real World Code Tree Search Execution Based

November 6, 2024

A Multilingual Sentiment Lexicon for Low-Resource Language Translation using Large Languages Models and Explainable AI
Melusi Malinga, Isaac Lupanda, Mike Wa Nkongolo, Phil van Deventer
Large Language Model Explainable AI Low Resource Sentiment Polarity Bidirectional Encoder Representation From Transformer Multilingual Sentiment Multilingual Context
Unfair Alignment: Examining Safety Alignment Across Vision Encoder Layers in Vision-Language Models
Saketh Bachu, Erfan Shayegani, Trishna Chakraborty, Rohit Lal, Arindam Dutta, Chengyu Song, Yue Dong, Nael Abu-Ghazaleh, Amit K. Roy-Chowdhury
Large Language Model Vision Language Model Multi Layer Safety Alignment Last Layer
Language Models are Hidden Reasoners: Unlocking Latent Reasoning Capabilities via Self-Rewarding
Haolin Chen, Yihao Feng, Zuxin Liu, Weiran Yao, Akshara Prabhakar, Shelby Heinecke, Ricky Ho, Phil Mui, Silvio Savarese, Caiming Xiong, Huan Wang
Large Language Model Language Model Reasoning Capability Capability Evolution Complex Reasoning Task Contrastive Reasoner
LSHBloom: Memory-efficient, Extreme-scale Document Deduplication
Arham Khan, Robert Underwood, Carlo Siebenschuh, Yadu Babuji, Aswathy Ajith, Kyle Hippe, Ozan Gokdemir, Alexander Brace, Kyle Chard, Ian Foster
Large Language Model Data Deduplication Memory effIcieNt
Multimodal Structure-Aware Quantum Data Processing
Hala Hawashin, Mehrnoosh Sadrzadeh
Large Language Model Natural Language Processing NLP Field Image Text Multimodal
PhDGPT: Introducing a psychometric and linguistic dataset about how large language models perceive graduate students and professors in psychology
Edoardo Sebastiano De Duro, Enrique Taietta, Riccardo Improta, Massimo Stella
Large Language Model Psychometric Property Psychological Phenomenon Machine Psychology
Bottom-Up and Top-Down Analysis of Values, Agendas, and Observations in Corpora and LLMs
Scott E. Friedman, Noam Benkler, Drisana Mosaphir, Jeffrey Rye, Sonja M. Schmer-Galunder, Micah Goldwater, Matthew McLure, Ruta Wheelock, Jeremy Gottlieb, Robert P. Goldman, Christopher Miller
Large Language Model Large Corpus Task Scheduling LLM Generated Policy Value Persuasive Argument
Medical Adaptation of Large Language and Vision-Language Models: Are We Making Progress?
Daniel P. Jeong, Saurabh Garg, Zachary C. Lipton, Michael Oberst
Large Language Model Vision Language Model Large Language Much Progress Domain Specific Model Biomedical Corpus Medical Task Adaptation
How Transformers Solve Propositional Logic Problems: A Mechanistic Analysis
Guan Zhe Hong, Nishanth Dikkala, Enming Luo, Cyrus Rashtchian, Rina Panigrahy
Large Language Model Transformer Megatron Decepticons General Analysis Complex Reasoning Logic Reasoning Layer Transformer
Fine-Grained Guidance for Retrievers: Leveraging LLMs' Feedback in Retrieval-Augmented Generation
Yuhang Liu, Xueyu Hu, Shengyu Zhang, Jingyuan Chen, Fan Wu, Fei Wu
Large Language Model Retrieval Augmented Generation Human Feedback Dense Retriever Hybrid Retriever
Polynomial Composition Activations: Unleashing the Dynamics of Large Language Models
Zhijian Zhuo, Ya Wang, Yutao Zeng, Xiaoqing Li, Xun Zhou, Jinwen Ma
Large Language Model Language Model Transformer Architecture Nonlinear Model Polynomial Activation Representational Capacity
MEG: Medical Knowledge-Augmented Large Language Models for Question Answering
Laura Cabello, Carmen Martin-Turrero, Uchenna Akujuobi, Anders Søgaard, Carlos Bobed
Large Language Model Question Answering Yes No Question Knowledge Graph Embeddings Language Understanding Task

Large Language Model

Papers

Bayesian Calibration of Win Rate Estimation with LLM Evaluators

Variational Low-Rank Adaptation Using IVON

Leveraging LLMs to Enable Natural Language Search on Go-to-market Platforms

Unlearning in- vs. out-of-distribution data in LLMs under gradient-based method

Benchmarking Large Language Models with Integer Sequence Generation Tasks

Measuring short-form factuality in large language models

Robust and Efficient Fine-tuning of LLMs with Bayesian Reparameterization of Low-Rank Adaptation

CodeTree: Agent-guided Tree Search for Code Generation with Large Language Models

A Multilingual Sentiment Lexicon for Low-Resource Language Translation using Large Languages Models and Explainable AI

Unfair Alignment: Examining Safety Alignment Across Vision Encoder Layers in Vision-Language Models

Language Models are Hidden Reasoners: Unlocking Latent Reasoning Capabilities via Self-Rewarding

LSHBloom: Memory-efficient, Extreme-scale Document Deduplication

Multimodal Structure-Aware Quantum Data Processing

PhDGPT: Introducing a psychometric and linguistic dataset about how large language models perceive graduate students and professors in psychology

Bottom-Up and Top-Down Analysis of Values, Agendas, and Observations in Corpora and LLMs

Medical Adaptation of Large Language and Vision-Language Models: Are We Making Progress?

How Transformers Solve Propositional Logic Problems: A Mechanistic Analysis

Fine-Grained Guidance for Retrievers: Leveraging LLMs' Feedback in Retrieval-Augmented Generation

Polynomial Composition Activations: Unleashing the Dynamics of Large Language Models

MEG: Medical Knowledge-Augmented Large Language Models for Question Answering