Cover Image

SMARTER: A Data-efficient Framework to Improve Toxicity Detection with Explanation via Self-augmenting Large Language Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Nghiem, Huy, Sachdeva, Advik, Daumé III, Hal
Format:	Preprint
Published:	2025
Subjects:	Computation and Language Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

HateCOT: An Explanation-Enhanced Dataset for Generalizable Offensive Speech Detection via Large Language Models
by: Nghiem, Huy, et al.
Published: (2024)

"You Gotta be a Doctor, Lin": An Investigation of Name-Based Bias of Large Language Models in Employment Recommendations
by: Nghiem, Huy, et al.
Published: (2024)

A Necessary Step toward Faithfulness: Measuring and Improving Consistency in Free-Text Explanations
by: Zhao, Lingjun, et al.
Published: (2025)

Bias in the Tails: How Name-conditioned Evaluative Framing in Resume Summaries Destabilizes LLM-based Hiring
by: Nghiem, Huy, et al.
Published: (2026)

Balancing Safety and Helpfulness in Healthcare AI Assistants through Iterative Preference Alignment
by: Nghiem, Huy, et al.
Published: (2025)

Language Models Predict Empathy Gaps Between Social In-groups and Out-groups
by: Hou, Yu, et al.
Published: (2025)

Steering Safely or Off a Cliff? Rethinking Specificity and Robustness in Inference-Time Interventions
by: Goyal, Navita, et al.
Published: (2026)

Toxicity Detection is NOT all you Need: Measuring the Gaps to Supporting Volunteer Content Moderators
by: Cao, Yang Trista, et al.
Published: (2023)

Successfully Guiding Humans with Imperfect Instructions by Highlighting Potential Errors and Suggesting Corrections
by: Zhao, Lingjun, et al.
Published: (2024)

Can Hallucination Correction Improve Video-Language Alignment?
by: Zhao, Lingjun, et al.
Published: (2025)

'Rich Dad, Poor Lad': How do Large Language Models Contextualize Socioeconomic Factors in College Admission ?
by: Nghiem, Huy, et al.
Published: (2025)

Pragmatics Meets Culture: Culturally-adapted Artwork Description Generation and Evaluation
by: Zhao, Lingjun, et al.
Published: (2026)

Do great minds think alike? Investigating Human-AI Complementarity in Question Answering with CAIMIRA
by: Gor, Maharshi, et al.
Published: (2024)

Reheat Nachos for Dinner? Evaluating AI Support for Cross-Cultural Communication of Neologisms
by: Ki, Dayeon, et al.
Published: (2026)

The Impact of Explanations on Fairness in Human-AI Decision-Making: Protected vs Proxy Features
by: Goyal, Navita, et al.
Published: (2023)

Anomaly Detection in Human Language via Meta-Learning: A Few-Shot Approach
by: Singla, Saurav, et al.
Published: (2025)

Can You Make It Sound Like You? Post-Editing LLM-Generated Text for Personal Style
by: Baumler, Connor, et al.
Published: (2026)

When Stereotypes GTG: The Impact of Predictive Text Suggestions on Gender Bias in Human-AI Co-Writing
by: Baumler, Connor, et al.
Published: (2024)

Diversity Boosts AI-Generated Text Detection
by: Basani, Advik Raj, et al.
Published: (2025)

Characterising Toxicity in Generative Large Language Models
by: Zhang, Zhiyao, et al.
Published: (2026)

Realistic Evaluation of Toxicity in Large Language Models
by: Luong, Tinh Son, et al.
Published: (2024)

LLMCheckup: Conversational Examination of Large Language Models via Interpretability Tools and Self-Explanations
by: Wang, Qianli, et al.
Published: (2024)

Natural Language Inference Improves Compositionality in Vision-Language Models
by: Cascante-Bonilla, Paola, et al.
Published: (2024)

Exploring Iterative Enhancement for Improving Learnersourced Multiple-Choice Question Explanations with Large Language Models
by: Bao, Qiming, et al.
Published: (2023)

A Survey of State of the Art Large Vision Language Models: Alignment, Benchmark, Evaluations and Challenges
by: Li, Zongxia, et al.
Published: (2025)

Improving Faithfulness of Large Language Models in Summarization via Sliding Generation and Self-Consistency
by: Li, Taiji, et al.
Published: (2024)

Advancing Large Language Model Attribution through Self-Improving
by: Huang, Lei, et al.
Published: (2024)

Athena: Retrieval-augmented Legal Judgment Prediction with Large Language Models
by: Peng, Xiao, et al.
Published: (2024)

Towards Efficient Large Language Models for Scientific Text: A Review
by: To, Huy Quoc, et al.
Published: (2024)

Natural Language Counterfactual Explanations for Graphs Using Large Language Models
by: Giorgi, Flavio, et al.
Published: (2024)

Efficient Detection of Toxic Prompts in Large Language Models
by: Liu, Yi, et al.
Published: (2024)

Characterizing Large Language Model Geometry Helps Solve Toxicity Detection and Generation
by: Balestriero, Randall, et al.
Published: (2023)

Large Language Models Can Self-Improve in Long-context Reasoning
by: Li, Siheng, et al.
Published: (2024)

Importance Weighting Can Help Large Language Models Self-Improve
by: Jiang, Chunyang, et al.
Published: (2024)

Beyond Accuracy: The Role of Calibration in Self-Improving Large Language Models
by: Huang, Liangjie, et al.
Published: (2025)

ELAD: Explanation-Guided Large Language Models Active Distillation
by: Zhang, Yifei, et al.
Published: (2024)

CogniDual Framework: Self-Training Large Language Models within a Dual-System Theoretical Framework for Improving Cognitive Tasks
by: Deng, Yongxin, et al.
Published: (2024)

A Novel Self-Evolution Framework for Large Language Models
by: Sun, Haoran, et al.
Published: (2025)

PEDANTS: Cheap but Effective and Interpretable Answer Equivalence
by: Li, Zongxia, et al.
Published: (2024)

Clickbait Detection via Large Language Models
by: Wang, Han, et al.
Published: (2023)