Cover Image

Truth Forest: Toward Multi-Scale Truthfulness in Large Language Models through Intervention without Tuning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Chen, Zhongzhi, Sun, Xingwu, Jiao, Xianfeng, Lian, Fengzong, Kang, Zhanhui, Wang, Di, Xu, Cheng-Zhong
Format:	Preprint
Published:	2023
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

Diverse and Fine-Grained Instruction-Following Ability Exploration with Synthetic Data
by: Gu, Zihui, et al.
Published: (2024)

Adaptive Activation Steering: A Tuning-Free LLM Truthfulness Improvement Method for Diverse Hallucinations Categories
by: Wang, Tianlong, et al.
Published: (2024)

Exploring Forgetting in Large Language Model Pre-Training
by: Liao, Chonghua, et al.
Published: (2024)

TruthPrInt: Mitigating Large Vision-Language Models Object Hallucination Via Latent Truthful-Guided Pre-Intervention
by: Duan, Jinhao, et al.
Published: (2025)

Ranking Large Language Models without Ground Truth
by: Dhurandhar, Amit, et al.
Published: (2024)

Mitigating Hallucination in Multimodal Large Language Model via Hallucination-targeted Direct Preference Optimization
by: Fu, Yuhan, et al.
Published: (2024)

Language Models "Grok" to Copy
by: Lv, Ang, et al.
Published: (2024)

Enhanced Language Model Truthfulness with Learnable Intervention and Uncertainty Expression
by: Bayat, Farima Fatahi, et al.
Published: (2024)

TruthX: Alleviating Hallucinations by Editing Large Language Models in Truthful Space
by: Zhang, Shaolei, et al.
Published: (2024)

Continuous Speech Tokenizer in Text To Speech
by: Li, Yixing, et al.
Published: (2024)

From Yes-Men to Truth-Tellers: Addressing Sycophancy in Large Language Models with Pinpoint Tuning
by: Chen, Wei, et al.
Published: (2024)

Towards Reliable Truth-Aligned Uncertainty Estimation in Large Language Models
by: Srey, Ponhvoan, et al.
Published: (2026)

Truth Knows No Language: Evaluating Truthfulness Beyond English
by: Figueras, Blanca Calvo, et al.
Published: (2025)

The Climb Carves Wisdom Deeper Than the Summit: On the Noisy Rewards in Learning to Reason
by: Lv, Ang, et al.
Published: (2025)

When Truth Is Overridden: Uncovering the Internal Origins of Sycophancy in Large Language Models
by: Wang, Keyu, et al.
Published: (2025)

Representational and Behavioral Stability of Truth in Large Language Models
by: Dies, Samantha, et al.
Published: (2025)

Re-Search for The Truth: Multi-round Retrieval-augmented Large Language Models are Strong Fake News Detectors
by: Li, Guanghua, et al.
Published: (2024)

TruthTorchLM: A Comprehensive Library for Predicting Truthfulness in LLM Outputs
by: Yaldiz, Duygu Nur, et al.
Published: (2025)

KatotohananQA: Evaluating Truthfulness of Large Language Models in Filipino
by: Nery, Lorenzo Alfred, et al.
Published: (2025)

Unconditional Truthfulness: Learning Unconditional Uncertainty of Large Language Models
by: Vazhentsev, Artem, et al.
Published: (2024)

Toward Reliable Scientific Hypothesis Generation: Evaluating Truthfulness and Hallucination in Large Language Models
by: Xiong, Guangzhi, et al.
Published: (2025)

Truth Neurons
by: Li, Haohang, et al.
Published: (2025)

The Trilemma of Truth in Large Language Models
by: Savcisens, Germans, et al.
Published: (2025)

Large Language Model Empowered Recommendation Meets All-domain Continual Pre-Training
by: Ma, Haokai, et al.
Published: (2025)

Large Language Models Are Involuntary Truth-Tellers: Exploiting Fallacy Failure for Jailbreak Attacks
by: Zhou, Yue, et al.
Published: (2024)

Enhancing Fact Retrieval in PLMs through Truthfulness
by: Youssef, Paul, et al.
Published: (2024)

TruthStance: An Annotated Dataset of Conversations on Truth Social
by: Ameen, Fathima, et al.
Published: (2026)

Inference-Time Intervention: Eliciting Truthful Answers from a Language Model
by: Li, Kenneth, et al.
Published: (2023)

Debating Truth: Debate-driven Claim Verification with Multiple Large Language Model Agents
by: He, Haorui, et al.
Published: (2025)

Adaptive Termination for Multi-round Parallel Reasoning: An Universal Semantic Entropy-Guided Framework
by: Xu, Zenan, et al.
Published: (2025)

Non-Linear Inference Time Intervention: Improving LLM Truthfulness
by: Hoscilowicz, Jakub, et al.
Published: (2024)

On the Universal Truthfulness Hyperplane Inside LLMs
by: Liu, Junteng, et al.
Published: (2024)

TruthRL: Incentivizing Truthful LLMs via Reinforcement Learning
by: Wei, Zhepei, et al.
Published: (2025)

PhD: A ChatGPT-Prompted Visual hallucination Evaluation Dataset
by: Liu, Jiazhen, et al.
Published: (2024)

Characterizing Truthfulness in Large Language Model Generations with Local Intrinsic Dimension
by: Yin, Fan, et al.
Published: (2024)

TruthEval: A Dataset to Evaluate LLM Truthfulness and Reliability
by: Khatun, Aisha, et al.
Published: (2024)

Pruning Weights but Not Truth: Safeguarding Truthfulness While Pruning LLMs
by: Fu, Yao, et al.
Published: (2025)

Balancing Stylization and Truth via Disentangled Representation Steering
by: Shen, Chenglei, et al.
Published: (2025)

To Tell The Truth: Language of Deception and Language Models
by: Hazra, Sanchaita, et al.
Published: (2023)

Emergence of Linear Truth Encodings in Language Models
by: Ravfogel, Shauli, et al.
Published: (2025)