:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Zhao, Theodore, Wei, Mu, Preston, J. Samuel, Poon, Hoifung
Format:	Preprint
Published:	2023
Subjects:	Computation and Language Machine Learning
Online Access:	https://arxiv.org/abs/2306.16564
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Offset Unlearning for Large Language Models
by: Huang, James Y., et al.
Published: (2024)

mDPO: Conditional Preference Optimization for Multimodal Large Language Models
by: Wang, Fei, et al.
Published: (2024)

Be My Eyes: Extending Large Language Models to New Modalities Through Multi-Agent Collaboration
by: Huang, James Y., et al.
Published: (2025)

X-Reasoner: Towards Generalizable Reasoning Across Modalities and Domains
by: Liu, Qianchu, et al.
Published: (2025)

From Introspection to Best Practices: Principled Analysis of Demonstrations in Multimodal In-Context Learning
by: Xu, Nan, et al.
Published: (2024)

Exploring Scaling Laws for EHR Foundation Models
by: Zhang, Sheng, et al.
Published: (2025)

ArenaBencher: Automatic Benchmark Evolution via Multi-Model Competitive Evaluation
by: Liu, Qin, et al.
Published: (2025)

Jailbreak-Zero: A Path to Pareto Optimal Red Teaming for Large Language Models
by: Hu, Kai, et al.
Published: (2025)

Semantic-Clipping: Efficient Vision-Language Modeling with Semantic-Guidedd Visual Selection
by: Li, Bangzheng, et al.
Published: (2025)

RULE: Reinforcement UnLEarning Achieves Forget-Retain Pareto Optimality
by: Zhang, Chenlong, et al.
Published: (2025)

ParetoHqD: Fast Offline Multiobjective Alignment of Large Language Models using Pareto High-quality Data
by: Gu, Haoran, et al.
Published: (2025)

Learning Sparse Visual Representations via Spatial-Semantic Factorization
by: Zhao, Theodore Zhengde, et al.
Published: (2026)

MetaScale: Test-Time Scaling with Evolving Meta-Thoughts
by: Liu, Qin, et al.
Published: (2025)

OmniStruct: Universal Text-to-Structure Generation across Diverse Schemas
by: Huang, James Y., et al.
Published: (2025)

Pareto Multi-Objective Alignment for Language Models
by: He, Qiang, et al.
Published: (2025)

UniversalNER: Targeted Distillation from Large Language Models for Open Named Entity Recognition
by: Zhou, Wenxuan, et al.
Published: (2023)

Correlated Errors in Large Language Models
by: Kim, Elliot, et al.
Published: (2025)

Uncertainty Quantification for In-Context Learning of Large Language Models
by: Ling, Chen, et al.
Published: (2024)

Self-Improvement Towards Pareto Optimality: Mitigating Preference Conflicts in Multi-Objective Alignment
by: Li, Moxin, et al.
Published: (2025)

Are Large Language Models Sensitive to the Motives Behind Communication?
by: Wu, Addison J., et al.
Published: (2025)

Rethinking Pruning Large Language Models: Benefits and Pitfalls of Reconstruction Error Minimization
by: Shin, Sungbin, et al.
Published: (2024)

Learning and Forgetting Unsafe Examples in Large Language Models
by: Zhao, Jiachen, et al.
Published: (2023)

Rational Metareasoning for Large Language Models
by: De Sabbata, C. Nicolò, et al.
Published: (2024)

Improving Large Language Model Safety with Contrastive Representation Learning
by: Simko, Samuel, et al.
Published: (2025)

CEQuest: Benchmarking Large Language Models for Construction Estimation
by: Wu, Yanzhao, et al.
Published: (2025)

Distilling Large Language Models for Text-Attributed Graph Learning
by: Pan, Bo, et al.
Published: (2024)

How do Large Language Models Navigate Conflicts between Honesty and Helpfulness?
by: Liu, Ryan, et al.
Published: (2024)

Training Optimal Large Diffusion Language Models
by: Ni, Jinjie, et al.
Published: (2025)

CLUE: Concept-Level Uncertainty Estimation for Large Language Models
by: Wang, Yu-Hsiang, et al.
Published: (2024)

Concurrent Linguistic Error Detection (CLED): a New Methodology for Error Detection in Large Language Models
by: Zhu, Jinhua, et al.
Published: (2024)

Advancing Tool-Augmented Large Language Models: Integrating Insights from Errors in Inference Trees
by: Chen, Sijia, et al.
Published: (2024)

DynaAct: Large Language Model Reasoning with Dynamic Action Spaces
by: Zhao, Xueliang, et al.
Published: (2025)

Paraphrase and Aggregate with Large Language Models for Minimizing Intent Classification Errors
by: Yadav, Vikas, et al.
Published: (2024)

BiSup: Bidirectional Quantization Error Suppression for Large Language Models
by: Zou, Minghui, et al.
Published: (2024)

Boosting of Thoughts: Trial-and-Error Problem Solving with Large Language Models
by: Chen, Sijia, et al.
Published: (2024)

Estimating Item Difficulty Using Large Language Models and Tree-Based Machine Learning Algorithms
by: Razavi, Pooya, et al.
Published: (2025)

Realised Volatility Forecasting: Machine Learning via Financial Word Embedding
by: Rahimikia, Eghbal, et al.
Published: (2021)

Disentangling Exploration of Large Language Models by Optimal Exploitation
by: Grams, Tim, et al.
Published: (2025)

DaMoC: Efficiently Selecting the Optimal Large Language Model for Fine-tuning Domain Tasks Based on Data and Model Compression
by: Huang, Wei, et al.
Published: (2025)

The Role of Diversity in In-Context Learning for Large Language Models
by: Xiao, Wenyang, et al.
Published: (2025)