Cover Image

Finetuning Language Models to Emit Linguistic Expressions of Uncertainty

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Chaudhry, Arslan, Thiagarajan, Sridhar, Gorur, Dilan
Format:	Preprint
Published:	2024
Subjects:	Computation and Language Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Improving Latent Generalization Using Test-time Compute
by: Chaudhry, Arslan, et al.
Published: (2026)

Perceptions of Linguistic Uncertainty by Language Models and Humans
by: Belem, Catarina G, et al.
Published: (2024)

Recursive Concept Evolution for Compositional Reasoning in Large Language Models
by: Chaudhry, Sarim
Published: (2026)

Ensembling Finetuned Language Models for Text Classification
by: Arango, Sebastian Pineda, et al.
Published: (2024)

Transfer Learning for Finetuning Large Language Models
by: Strangmann, Tobias, et al.
Published: (2024)

Improving Multilingual Instruction Finetuning via Linguistically Natural and Diverse Datasets
by: Indurthi, Sathish Reddy, et al.
Published: (2024)

Towards Active Synthetic Data Generation for Finetuning Language Models
by: Kessler, Samuel, et al.
Published: (2025)

MetaFaith: Faithful Natural Language Uncertainty Expression in LLMs
by: Liu, Gabrielle Kaili-May, et al.
Published: (2025)

Large Language Models to Diffusion Finetuning
by: Cetin, Edoardo, et al.
Published: (2025)

When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method
by: Zhang, Biao, et al.
Published: (2024)

ApiQ: Finetuning of 2-Bit Quantized Large Language Model
by: Liao, Baohao, et al.
Published: (2024)

CoBa: Convergence Balancer for Multitask Finetuning of Large Language Models
by: Gong, Zi, et al.
Published: (2024)

MuonAll: Muon Variant for Efficient Finetuning of Large Language Models
by: Page, Saurabh, et al.
Published: (2025)

Latent learning: episodic memory complements parametric learning by enabling flexible reuse of experiences
by: Lampinen, Andrew Kyle, et al.
Published: (2025)

Inference-Aware Fine-Tuning for Best-of-N Sampling in Large Language Models
by: Chow, Yinlam, et al.
Published: (2024)

ReFT: Representation Finetuning for Language Models
by: Wu, Zhengxuan, et al.
Published: (2024)

Vanishing Gradients in Reinforcement Finetuning of Language Models
by: Razin, Noam, et al.
Published: (2023)

Is AI Catching Up to Human Expression? Exploring Emotion, Personality, Authorship, and Linguistic Style in English and Arabic with Six Large Language Models
by: Alsadhan, Nasser A
Published: (2026)

Chameleon: A Flexible Data-mixing Framework for Language Model Pretraining and Finetuning
by: Xie, Wanyun, et al.
Published: (2025)

Power-Law Decay Loss for Large Language Model Finetuning: A Theory Perspective
by: Shao, Jintian
Published: (2025)

Unfamiliar Finetuning Examples Control How Language Models Hallucinate
by: Kang, Katie, et al.
Published: (2024)

Transfer Learning of Tabular Data by Finetuning Large Language Models
by: Rabbani, Shourav B., et al.
Published: (2025)

Multilingual Language Models Encode Script Over Linguistic Structure
by: Verma, Aastha A K, et al.
Published: (2026)

Towards Linguistically-Aware and Language-Independent Tokenization for Large Language Models (LLMs)
by: Rahman, Abrar, et al.
Published: (2024)

LQ-LoRA: Low-rank Plus Quantized Matrix Decomposition for Efficient Language Model Finetuning
by: Guo, Han, et al.
Published: (2023)

Sparse Memory Finetuning as a Low-Forgetting Alternative to LoRA and Full Finetuning
by: Gupta, Prakhar, et al.
Published: (2026)

Predicting Emergent Capabilities by Finetuning
by: Snell, Charlie, et al.
Published: (2024)

Improving Sparse Memory Finetuning
by: Goyal, Satyam, et al.
Published: (2026)

Generalizable and Stable Finetuning of Pretrained Language Models on Low-Resource Texts
by: Somayajula, Sai Ashish, et al.
Published: (2024)

General Preference Reinforcement Learning
by: Umer, Muhammad, et al.
Published: (2026)

Uncertainty in Semantic Language Modeling with PIXELS
by: Radu, Stefania, et al.
Published: (2025)

The Illusionist's Prompt: Exposing the Factual Vulnerabilities of Large Language Models with Linguistic Nuances
by: Wang, Yining, et al.
Published: (2025)

Internalizing World Models via Self-Play Finetuning for Agentic RL
by: Chen, Shiqi, et al.
Published: (2025)

Differentially Private Zeroth-Order Methods for Scalable Large Language Model Finetuning
by: Liu, Z, et al.
Published: (2024)

An Experimental Design Framework for Label-Efficient Supervised Finetuning of Large Language Models
by: Bhatt, Gantavya, et al.
Published: (2024)

Sparse Upcycling: Inference Inefficient Finetuning
by: Doubov, Sasha, et al.
Published: (2024)

Understanding Finetuning for Factual Knowledge Extraction
by: Ghosal, Gaurav, et al.
Published: (2024)

Diffusion Language Models Can Perform Many Tasks with Scaling and Instruction-Finetuning
by: Ye, Jiasheng, et al.
Published: (2023)

Linguistic Blind Spots of Large Language Models
by: Cheng, Jiali, et al.
Published: (2025)

Decoding Uncertainty: The Impact of Decoding Strategies for Uncertainty Estimation in Large Language Models
by: Hashimoto, Wataru, et al.
Published: (2025)