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

October 15, 2024

Scaling laws for post-training quantized large language models
Zifei Xu, Alexander Lan, Wanzin Yazar, Tristan Webb, Sayeh Sharify, Xin Wang
Large Language Model Large Pre Trained Language Model Loss Landscape Weight Quantization Scaling Factor
Planning Anything with Rigor: General-Purpose Zero-Shot Planning with LLM-based Formalized Programming
Yilun Hao, Yang Zhang, Chuchu Fan
Large Language Model Zero Shot Long Horizon Task Planning Problem Rigorous Framework
Bridging Large Language Models and Graph Structure Learning Models for Robust Representation Learning
Guangxin Su, Yifan Zhu, Wenjie Zhang, Hanchen Wang, Ying Zhang
Large Language Model Graph Representation Learning Graph Structure Learning Robust Representation Learning Informative Latent Representation
Generative AI's aggregated knowledge versus web-based curated knowledge
Ted Selker, Yunzi Wu
Large Language Model Generative AI Knowledge Based Knowledge Aggregation Knowledge Exploration
Beyond the Comfort Zone: Emerging Solutions to Overcome Challenges in Integrating LLMs into Software Products
Nadia Nahar, Christian Kästner, Jenna Butler, Chris Parnin, Thomas Zimmermann, Christian Bird
Large Language Model Technical Challenge Software System Software Development User Perception New Solution
MoE-Pruner: Pruning Mixture-of-Experts Large Language Model using the Hints from Its Router
Yanyue Xie, Zhi Zhang, Ding Zhou, Cong Xie, Ziang Song, Xin Liu, Yanzhi Wang, Xue Lin, An Xu
Large Language Model Mixture of Expert Edge Pruning Natural Language Hint
Impacts of Continued Legal Pre-Training and IFT on LLMs' Latent Representations of Human-Defined Legal Concepts
Shaun Ho
Large Language Model Pre Training Meaningful Representation Legal Text Intermediate Latent Legal Corpus Complex Legal
SGEdit: Bridging LLM with Text2Image Generative Model for Scene Graph-based Image Editing
Zhiyuan Zhang, DongDong Chen, Jing Liao
Large Language Model Image Editing Scene Graph Scene Structure Text to Image Generative Model Dynamic Attention Guided Diffusion
NesTools: A Dataset for Evaluating Nested Tool Learning Abilities of Large Language Models
Han Han, Tong Zhu, Xiang Zhang, Mengsong Wu, Hao Xiong, Wenliang Chen
Large Language Model Data Set Tool Learning
FoundTS: Comprehensive and Unified Benchmarking of Foundation Models for Time Series Forecasting
Zhe Li, Xiangfei Qiu, Peng Chen, Yihang Wang, Hanyin Cheng, Yang Shu, Jilin Hu, Chenjuan Guo, Aoying Zhou, Qingsong Wen, Christian S. Jensen, Bin Yang
Large Language Model Foundation Model Time Series Forecasting Evaluation Benchmark Unseen Data Forecasting Method Time Series Forecasting Model
Language Models Encode Numbers Using Digit Representations in Base 10
Amit Arnold Levy, Mor Geva
Large Language Model Numerical Reasoning Numerical Result Human Base Number Representation Circle Representation
Personas with Attitudes: Controlling LLMs for Diverse Data Annotation
Leon Fröhling, Gianluca Demartini, Dennis Assenmacher
Large Language Model Multi Annotator Persona Information Strong Annotation
DySpec: Faster Speculative Decoding with Dynamic Token Tree Structure
Yunfan Xiong, Ruoyu Zhang, Yanzeng Li, Tianhao Wu, Lei Zou
Large Language Model Speculative Decoding Token Generation Speculative Execution Aberrant Behavior
Converging to a Lingua Franca: Evolution of Linguistic Regions and Semantics Alignment in Multilingual Large Language Models
Hongchuan Zeng, Senyu Han, Lu Chen, Kai Yu
Large Language Model Latent Space Multilingual Large Language Model Semantic Alignment Language Agnostic Language Community Network Convergence
IntGrad MT: Eliciting LLMs' Machine Translation Capabilities with Sentence Interpolation and Gradual MT
Seung-Woo Choi, Ga-Hyun Yoo, Jay-Yoon Lee
Large Language Model Machine Translation Parallel Corpus Recent Large Language Model Low Resource Language Pair Gradual Pattern
Retrieval Augmented Spelling Correction for E-Commerce Applications
Xuan Guo, Rohit Patki, Dante Everaert, Christopher Potts
Large Language Model Retrieval Augmented Generation E Commerce Retrieval Augmented Spelling Correction
Transformer Layer Injection: A Novel Approach for Efficient Upscaling of Large Language Models
James Vo
Large Language Model Transformer Based Model Novel Approach Transformer Layer Model Scale Effective Depth Up Scaling Arbitrary Upscaling
Measuring Spiritual Values and Bias of Large Language Models
Songyuan Liu, Ziyang Zhang, Runze Yan, Wei Wu, Carl Yang, Jiaying Lu
Large Language Model Large Corpus Absolute Stance Bias Cultural Value
Causal Reasoning in Large Language Models: A Knowledge Graph Approach
Yejin Kim, Eojin Kang, Juae Kim, H. Howie Huang
Large Language Model Knowledge Graph Reasoning Capability Random Walk Causal Reasoning Knowledge Graph Reasoning
Y-Mol: A Multiscale Biomedical Knowledge-Guided Large Language Model for Drug Development
Tengfei Ma, Xuan Lin, Tianle Li, Chaoyi Li, Long Chen, Peng Zhou, Xibao Cai, Xinyu Yang, Daojian Zeng, Dongsheng Cao, Xiangxiang Zeng
Large Language Model Drug Discovery Drug Drug Interaction Drug Design Multiscale Modeling

Large Language Model

Papers

Scaling laws for post-training quantized large language models

Planning Anything with Rigor: General-Purpose Zero-Shot Planning with LLM-based Formalized Programming

Bridging Large Language Models and Graph Structure Learning Models for Robust Representation Learning

Generative AI's aggregated knowledge versus web-based curated knowledge

Beyond the Comfort Zone: Emerging Solutions to Overcome Challenges in Integrating LLMs into Software Products

MoE-Pruner: Pruning Mixture-of-Experts Large Language Model using the Hints from Its Router

Impacts of Continued Legal Pre-Training and IFT on LLMs' Latent Representations of Human-Defined Legal Concepts

SGEdit: Bridging LLM with Text2Image Generative Model for Scene Graph-based Image Editing

NesTools: A Dataset for Evaluating Nested Tool Learning Abilities of Large Language Models

FoundTS: Comprehensive and Unified Benchmarking of Foundation Models for Time Series Forecasting

Language Models Encode Numbers Using Digit Representations in Base 10

Personas with Attitudes: Controlling LLMs for Diverse Data Annotation

DySpec: Faster Speculative Decoding with Dynamic Token Tree Structure

Converging to a Lingua Franca: Evolution of Linguistic Regions and Semantics Alignment in Multilingual Large Language Models

IntGrad MT: Eliciting LLMs' Machine Translation Capabilities with Sentence Interpolation and Gradual MT

Retrieval Augmented Spelling Correction for E-Commerce Applications

Transformer Layer Injection: A Novel Approach for Efficient Upscaling of Large Language Models

Measuring Spiritual Values and Bias of Large Language Models

Causal Reasoning in Large Language Models: A Knowledge Graph Approach

Y-Mol: A Multiscale Biomedical Knowledge-Guided Large Language Model for Drug Development