:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Author:	Kim, Hazel H.
Format:	Preprint
Published:	2024
Subjects:	Computation and Language Machine Learning
Online Access:	https://arxiv.org/abs/2402.14337
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Can Language Models Perform Robust Reasoning in Chain-of-thought Prompting with Noisy Rationales?
by: Zhou, Zhanke, et al.
Published: (2024)

Structural Rationale Distillation via Reasoning Space Compression
by: Yang, Jialin, et al.
Published: (2026)

Comparison of Scoring Rationales Between Large Language Models and Human Raters
by: Hua, Haowei, et al.
Published: (2025)

Teaching Large Language Models Number-Focused Headline Generation With Key Element Rationales
by: Qian, Zhen, et al.
Published: (2025)

Self-Training Meets Consistency: Improving LLMs' Reasoning with Consistency-Driven Rationale Evaluation
by: Lee, Jaehyeok, et al.
Published: (2024)

Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval
by: Ji, Luo, et al.
Published: (2024)

Aligning Attention with Human Rationales for Self-Explaining Hate Speech Detection
by: Eilertsen, Brage, et al.
Published: (2025)

Model Interpretability and Rationale Extraction by Input Mask Optimization
by: Brinner, Marc, et al.
Published: (2025)

InstructRAG: Instructing Retrieval-Augmented Generation via Self-Synthesized Rationales
by: Wei, Zhepei, et al.
Published: (2024)

Towards Interpretable Hate Speech Detection using Large Language Model-extracted Rationales
by: Nirmal, Ayushi, et al.
Published: (2024)

SaySelf: Teaching LLMs to Express Confidence with Self-Reflective Rationales
by: Xu, Tianyang, et al.
Published: (2024)

Empirical Characterization of Rationale Stability Under Controlled Perturbations for Explainable Pattern Recognition
by: Sakib, Abu Noman Md, et al.
Published: (2026)

Efficient Rationale-based Retrieval: On-policy Distillation from Generative Rerankers based on JEPA
by: Chen, Teng, et al.
Published: (2026)

Exploring the Trade-off Between Model Performance and Explanation Plausibility of Text Classifiers Using Human Rationales
by: Resck, Lucas E., et al.
Published: (2024)

Reasoning, Code, or Both? How Large Language Models Handle Variations in Math Questions
by: Kutakh, Matthew
Published: (2026)

Investigating the Impact of Rationales for LLMs on Natural Language Understanding
by: Shi, Wenhang, et al.
Published: (2025)

Theoretical Rationale of the Language Experience Approach.
by: Stauffer, Russell G.
Published: (1971)

On the Generalizability of "Competition of Mechanisms: Tracing How Language Models Handle Facts and Counterfactuals"
by: Dotsinski, Asen, et al.
Published: (2025)

Reason2Decide: Rationale-Driven Multi-Task Learning
by: Hasan, H M Quamran, et al.
Published: (2025)

Verbosity-Aware Rationale Reduction: Effective Reduction of Redundant Rationale via Principled Criteria
by: Jang, Joonwon, et al.
Published: (2024)

RL for Reasoning by Adaptively Revealing Rationales
by: Amani, Mohammad Hossein, et al.
Published: (2025)

Rationales Are Not Silver Bullets: Measuring the Impact of Rationales on Model Performance and Reliability
by: Zhu, Chiwei, et al.
Published: (2025)

On Uncertainty In Natural Language Processing
by: Ulmer, Dennis
Published: (2024)

MARE: Multi-Aspect Rationale Extractor on Unsupervised Rationale Extraction
by: Jiang, Han, et al.
Published: (2024)

Fragile Thoughts: How Large Language Models Handle Chain-of-Thought Perturbations
by: Aravindan, Ashwath Vaithinathan, et al.
Published: (2026)

Reasoning-Grounded Natural Language Explanations for Language Models
by: Cahlik, Vojtech, et al.
Published: (2025)

Uncertainty Estimation and Quantification for LLMs: A Simple Supervised Approach
by: Liu, Linyu, et al.
Published: (2024)

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

Quantifying Uncertainty in Natural Language Explanations of Large Language Models for Question Answering
by: Li, Yangyi, et al.
Published: (2025)

Bypassing the Rationale: Causal Auditing of Implicit Reasoning in Language Models
by: Sathyanarayanan, Anish, et al.
Published: (2026)

How Uncertainty Estimation Scales with Sampling in Reasoning Models
by: Del, Maksym, et al.
Published: (2026)

GeoReasoner: Reasoning On Geospatially Grounded Context For Natural Language Understanding
by: Yan, Yibo, et al.
Published: (2024)

Simple Yet Effective: An Information-Theoretic Approach to Multi-LLM Uncertainty Quantification
by: Kruse, Maya, et al.
Published: (2025)

Tracing Uncertainty in Language Model "Reasoning"
by: Grünefeld, Nils, et al.
Published: (2026)

Rationale Behind Essay Scores: Enhancing S-LLM's Multi-Trait Essay Scoring with Rationale Generated by LLMs
by: Chu, SeongYeub, et al.
Published: (2024)

Simple Policy Gradients for Reasoning with Diffusion Language Models
by: Zhan, Anthony
Published: (2025)

Testing Uncertainty of Large Language Models for Physics Knowledge and Reasoning
by: Reganova, Elizaveta, et al.
Published: (2024)

FERA: Uncertainty-Aware Federated Reasoning for Large Language Models
by: Wang, Ruhan, et al.
Published: (2026)

Reasoning Pattern Matters: Learning to Reason without Human Rationales
by: Pang, Chaoxu, et al.
Published: (2025)

A Simple and Effective Pruning Approach for Large Language Models
by: Sun, Mingjie, et al.
Published: (2023)