Large Language Models are Geographically Biased
Fuente:
arXiv
Saved in:
| Main Authors: | Manvi, Rohin, Khanna, Samar, Burke, Marshall, Lobell, David, Ermon, Stefano |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
GeoLLM: Extracting Geospatial Knowledge from Large Language Models
by: Manvi, Rohin, et al.
Published: (2023)
by: Manvi, Rohin, et al.
Published: (2023)
Adaptive Inference-Time Compute: LLMs Can Predict if They Can Do Better, Even Mid-Generation
by: Manvi, Rohin, et al.
Published: (2024)
by: Manvi, Rohin, et al.
Published: (2024)
DiffusionSat: A Generative Foundation Model for Satellite Imagery
by: Khanna, Samar, et al.
Published: (2023)
by: Khanna, Samar, et al.
Published: (2023)
Empowering Many, Biasing a Few: Generalist Credit Scoring through Large Language Models
by: Feng, Duanyu, et al.
Published: (2023)
by: Feng, Duanyu, et al.
Published: (2023)
Subtle Biases Need Subtler Measures: Dual Metrics for Evaluating Representative and Affinity Bias in Large Language Models
by: Kumar, Abhishek, et al.
Published: (2024)
by: Kumar, Abhishek, et al.
Published: (2024)
Laissez-Faire Harms: Algorithmic Biases in Generative Language Models
by: Shieh, Evan, et al.
Published: (2024)
by: Shieh, Evan, et al.
Published: (2024)
ExPLoRA: Parameter-Efficient Extended Pre-Training to Adapt Vision Transformers under Domain Shifts
by: Khanna, Samar, et al.
Published: (2024)
by: Khanna, Samar, et al.
Published: (2024)
Relative Value Biases in Large Language Models
by: Hayes, William M., et al.
Published: (2024)
by: Hayes, William M., et al.
Published: (2024)
Large Language Models are Biased Reinforcement Learners
by: Hayes, William M., et al.
Published: (2024)
by: Hayes, William M., et al.
Published: (2024)
Zero-Overhead Introspection for Adaptive Test-Time Compute
by: Manvi, Rohin, et al.
Published: (2025)
by: Manvi, Rohin, et al.
Published: (2025)
Reward Models Inherit Value Biases from Pretraining
by: Christian, Brian, et al.
Published: (2026)
by: Christian, Brian, et al.
Published: (2026)
Mercury: Ultra-Fast Language Models Based on Diffusion
by: Labs, Inception, et al.
Published: (2025)
by: Labs, Inception, et al.
Published: (2025)
Hypothesis Generation with Large Language Models
by: Zhou, Yangqiaoyu, et al.
Published: (2024)
by: Zhou, Yangqiaoyu, et al.
Published: (2024)
Correlated Errors in Large Language Models
by: Kim, Elliot, et al.
Published: (2025)
by: Kim, Elliot, et al.
Published: (2025)
Psychological Counseling Ability of Large Language Models
by: Peng, Fangyu, et al.
Published: (2025)
by: Peng, Fangyu, et al.
Published: (2025)
Assessing Large Language Models on Climate Information
by: Bulian, Jannis, et al.
Published: (2023)
by: Bulian, Jannis, et al.
Published: (2023)
Are Models Biased on Text without Gender-related Language?
by: Belém, Catarina G, et al.
Published: (2024)
by: Belém, Catarina G, et al.
Published: (2024)
Foundational Challenges in Assuring Alignment and Safety of Large Language Models
by: Anwar, Usman, et al.
Published: (2024)
by: Anwar, Usman, et al.
Published: (2024)
A Taxonomy of Stereotype Content in Large Language Models
by: Nicolas, Gandalf, et al.
Published: (2024)
by: Nicolas, Gandalf, et al.
Published: (2024)
Transforming Agency. On the mode of existence of Large Language Models
by: Barandiaran, Xabier E., et al.
Published: (2024)
by: Barandiaran, Xabier E., et al.
Published: (2024)
Bias and Fairness in Large Language Models: A Survey
by: Gallegos, Isabel O., et al.
Published: (2023)
by: Gallegos, Isabel O., et al.
Published: (2023)
LangFair: A Python Package for Assessing Bias and Fairness in Large Language Model Use Cases
by: Bouchard, Dylan, et al.
Published: (2025)
by: Bouchard, Dylan, et al.
Published: (2025)
LLMCarbon: Modeling the end-to-end Carbon Footprint of Large Language Models
by: Faiz, Ahmad, et al.
Published: (2023)
by: Faiz, Ahmad, et al.
Published: (2023)
ResumeAtlas: Revisiting Resume Classification with Large-Scale Datasets and Large Language Models
by: Heakl, Ahmed, et al.
Published: (2024)
by: Heakl, Ahmed, et al.
Published: (2024)
Exploring Accuracy-Fairness Trade-off in Large Language Models
by: Zhang, Qingquan, et al.
Published: (2024)
by: Zhang, Qingquan, et al.
Published: (2024)
Are Large Language Models Chameleons? An Attempt to Simulate Social Surveys
by: Geng, Mingmeng, et al.
Published: (2024)
by: Geng, Mingmeng, et al.
Published: (2024)
Towards Large Language Models that Benefit for All: Benchmarking Group Fairness in Reward Models
by: Song, Kefan, et al.
Published: (2025)
by: Song, Kefan, et al.
Published: (2025)
REQUAL-LM: Reliability and Equity through Aggregation in Large Language Models
by: Ebrahimi, Sana, et al.
Published: (2024)
by: Ebrahimi, Sana, et al.
Published: (2024)
A Moral Imperative: The Need for Continual Superalignment of Large Language Models
by: Puthumanaillam, Gokul, et al.
Published: (2024)
by: Puthumanaillam, Gokul, et al.
Published: (2024)
Emissions and Performance Trade-off Between Small and Large Language Models
by: Garg, Anandita, et al.
Published: (2025)
by: Garg, Anandita, et al.
Published: (2025)
Richer Output for Richer Countries: Uncovering Geographical Disparities in Generated Stories and Travel Recommendations
by: Bhagat, Kirti, et al.
Published: (2024)
by: Bhagat, Kirti, et al.
Published: (2024)
GECOBench: A Gender-Controlled Text Dataset and Benchmark for Quantifying Biases in Explanations
by: Wilming, Rick, et al.
Published: (2024)
by: Wilming, Rick, et al.
Published: (2024)
Fairer Preferences Elicit Improved Human-Aligned Large Language Model Judgments
by: Zhou, Han, et al.
Published: (2024)
by: Zhou, Han, et al.
Published: (2024)
What's in a Name? Auditing Large Language Models for Race and Gender Bias
by: Salinas, Alejandro, et al.
Published: (2024)
by: Salinas, Alejandro, et al.
Published: (2024)
Large Language Models Assume People are More Rational than We Really are
by: Liu, Ryan, et al.
Published: (2024)
by: Liu, Ryan, et al.
Published: (2024)
Self-Debiasing Large Language Models: Zero-Shot Recognition and Reduction of Stereotypes
by: Gallegos, Isabel O., et al.
Published: (2024)
by: Gallegos, Isabel O., et al.
Published: (2024)
Predicting Learning Performance with Large Language Models: A Study in Adult Literacy
by: Zhang, Liang, et al.
Published: (2024)
by: Zhang, Liang, et al.
Published: (2024)
AXOLOTL: Fairness through Assisted Self-Debiasing of Large Language Model Outputs
by: Ebrahimi, Sana, et al.
Published: (2024)
by: Ebrahimi, Sana, et al.
Published: (2024)
SimBench: Benchmarking the Ability of Large Language Models to Simulate Human Behaviors
by: Hu, Tiancheng, et al.
Published: (2025)
by: Hu, Tiancheng, et al.
Published: (2025)
SUV: Scalable Large Language Model Copyright Compliance with Regularized Selective Unlearning
by: Xu, Tianyang, et al.
Published: (2025)
by: Xu, Tianyang, et al.
Published: (2025)
Similar Items
-
GeoLLM: Extracting Geospatial Knowledge from Large Language Models
by: Manvi, Rohin, et al.
Published: (2023) -
Adaptive Inference-Time Compute: LLMs Can Predict if They Can Do Better, Even Mid-Generation
by: Manvi, Rohin, et al.
Published: (2024) -
DiffusionSat: A Generative Foundation Model for Satellite Imagery
by: Khanna, Samar, et al.
Published: (2023) -
Empowering Many, Biasing a Few: Generalist Credit Scoring through Large Language Models
by: Feng, Duanyu, et al.
Published: (2023) -
Subtle Biases Need Subtler Measures: Dual Metrics for Evaluating Representative and Affinity Bias in Large Language Models
by: Kumar, Abhishek, et al.
Published: (2024)