:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Author:	Smilga, Veronika
Format:	Preprint
Published:	2025
Subjects:	Computation and Language
Online Access:	https://arxiv.org/abs/2501.06638
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

RuBia: A Russian Language Bias Detection Dataset
by: Grigoreva, Veronika, et al.
Published: (2024)

Smaller Language Models Are Better Instruction Evolvers
by: Hui, Tingfeng, et al.
Published: (2024)

Investigating Gender Bias in Turkish Language Models
by: Caglidil, Orhun Mersin, et al.
Published: (2024)

Smaller Large Language Models Can Do Moral Self-Correction
by: Liu, Guangliang, et al.
Published: (2024)

Distilling Multilingual Vision-Language Models: When Smaller Models Stay Multilingual
by: Sriratanawilai, Sukrit, et al.
Published: (2025)

Does Liking Yellow Imply Driving a School Bus? Semantic Leakage in Language Models
by: Gonen, Hila, et al.
Published: (2024)

Smaller Language Models are capable of selecting Instruction-Tuning Training Data for Larger Language Models
by: Mekala, Dheeraj, et al.
Published: (2024)

The Inverse Scaling Effect of Pre-Trained Language Model Surprisal Is Not Due to Data Leakage
by: Oh, Byung-Doh, et al.
Published: (2025)

Mixed Distillation Helps Smaller Language Model Better Reasoning
by: Li, Chenglin, et al.
Published: (2023)

Down the Toxicity Rabbit Hole: A Novel Framework to Bias Audit Large Language Models
by: Dutta, Arka, et al.
Published: (2023)

Improving Text Embeddings for Smaller Language Models Using Contrastive Fine-tuning
by: Ukarapol, Trapoom, et al.
Published: (2024)

Investigating Spatial Attention Bias in Vision-Language Models
by: Chaudhary, Aryan, et al.
Published: (2025)

On Bias and Fairness in NLP: Investigating the Impact of Bias and Debiasing in Language Models on the Fairness of Toxicity Detection
by: Elsafoury, Fatma, et al.
Published: (2023)

On Importance of Layer Pruning for Smaller BERT Models and Low Resource Languages
by: Shirke, Mayur, et al.
Published: (2025)

Investigating Implicit Bias in Large Language Models: A Large-Scale Study of Over 50 LLMs
by: Kumar, Divyanshu, et al.
Published: (2024)

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants
by: Zhang, Yiqun, et al.
Published: (2025)

Quantifying Association Capabilities of Large Language Models and Its Implications on Privacy Leakage
by: Shao, Hanyin, et al.
Published: (2023)

The Rise and Down of Babel Tower: Investigating the Evolution Process of Multilingual Code Large Language Model
by: Chen, Jiawei, et al.
Published: (2024)

DRAMA: Diverse Augmentation from Large Language Models to Smaller Dense Retrievers
by: Ma, Xueguang, et al.
Published: (2025)

Smaller Language Models are Better Black-box Machine-Generated Text Detectors
by: Mireshghallah, Niloofar, et al.
Published: (2023)

Teaching Smaller Language Models To Generalise To Unseen Compositional Questions (Full Thesis)
by: Hartill, Tim
Published: (2024)

MAGDi: Structured Distillation of Multi-Agent Interaction Graphs Improves Reasoning in Smaller Language Models
by: Chen, Justin Chih-Yao, et al.
Published: (2024)

Less is More: Making Smaller Language Models Competent Subgraph Retrievers for Multi-hop KGQA
by: Huang, Wenyu, et al.
Published: (2024)

GReaTer: Gradients over Reasoning Makes Smaller Language Models Strong Prompt Optimizers
by: Das, Sarkar Snigdha Sarathi, et al.
Published: (2024)

Hearing the Order: Investigating Position Bias in Large Audio-Language Models
by: Lin, Yu-Xiang, et al.
Published: (2025)

BiasDora: Exploring Hidden Biased Associations in Vision-Language Models
by: Raj, Chahat, et al.
Published: (2024)

Exploring Performance Contrasts in TableQA: Step-by-Step Reasoning Boosts Bigger Language Models, Limits Smaller Language Models
by: Yang, Haoyan, et al.
Published: (2024)

Persuasiveness and Bias in LLM: Investigating the Impact of Persuasiveness and Reinforcement of Bias in Language Models
by: Roy, Saumya
Published: (2025)

Where is the answer? Investigating Positional Bias in Language Model Knowledge Extraction
by: Saito, Kuniaki, et al.
Published: (2024)

VoiceBBQ: Investigating Effect of Content and Acoustics in Social Bias of Spoken Language Model
by: Choi, Junhyuk, et al.
Published: (2025)

Born With a Silver Spoon? Investigating Socioeconomic Bias in Large Language Models
by: Singh, Smriti, et al.
Published: (2024)

Skip-Thinking: Chunk-wise Chain-of-Thought Distillation Enable Smaller Language Models to Reason Better and Faster
by: Chen, Xiao, et al.
Published: (2025)

Tiny Titans: Can Smaller Large Language Models Punch Above Their Weight in the Real World for Meeting Summarization?
by: Fu, Xue-Yong, et al.
Published: (2024)

Distill Not Only Data but Also Rewards: Can Smaller Language Models Surpass Larger Ones?
by: Zhang, Yudi, et al.
Published: (2025)

SNEAK: Evaluating Strategic Communication and Information Leakage in Large Language Models
by: Avsian, Adar, et al.
Published: (2026)

Investigating Thinking Behaviours of Reasoning-Based Language Models for Social Bias Mitigation
by: Luo, Guoqing, et al.
Published: (2025)

Bias in, Bias out: Annotation Bias in Multilingual Large Language Models
by: Cui, Xia, et al.
Published: (2025)

Explicit vs. Implicit: Investigating Social Bias in Large Language Models through Self-Reflection
by: Zhao, Yachao, et al.
Published: (2025)

BiasConnect: Investigating Bias Interactions in Text-to-Image Models
by: Shukla, Pushkar, et al.
Published: (2025)

Benchmarking Benchmark Leakage in Large Language Models
by: Xu, Ruijie, et al.
Published: (2024)