Cover Image

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Fu, Yao, Long, Xianxuan, Li, Runchao, Yu, Haotian, Sheng, Mu, Han, Xiaotian, Yin, Yu, Li, Pan
Format:	Preprint
Published:	2025
Subjects:	Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

When Truthful Representations Flip Under Deceptive Instructions?
by: Long, Xianxuan, et al.
Published: (2025)

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

Dynamic Self-Distillation via Previous Mini-batches for Fine-tuning Small Language Models
by: Fu, Yao, et al.
Published: (2024)

FAEDKV: Infinite-Window Fourier Transform for Unbiased KV Cache Compression
by: Li, Runchao, et al.
Published: (2025)

Demystifying Hybrid Thinking: Can LLMs Truly Switch Between Think and No-Think?
by: Wang, Shouren, et al.
Published: (2025)

Fitting Is Not Enough: Smoothness in Extremely Quantized LLMs
by: Xu, Yuzhuang, et al.
Published: (2026)

SliderQuant: Accurate Post-Training Quantization for LLMs
by: Wang, Shigeng, et al.
Published: (2026)

Evaluating Quantized Large Language Models
by: Li, Shiyao, et al.
Published: (2024)

The Quantization Trap: Breaking Linear Scaling Laws in Multi-Hop Reasoning
by: Han, Henry, et al.
Published: (2026)

Disentangling Deception and Hallucination Failures in LLMs
by: Lu, Haolang, et al.
Published: (2026)

Quantization Meets dLLMs: A Systematic Study of Post-training Quantization for Diffusion LLMs
by: Lin, Haokun, et al.
Published: (2025)

Evaluating the Generalization Ability of Quantized LLMs: Benchmark, Analysis, and Toolbox
by: Liu, Yijun, et al.
Published: (2024)

Quantization Hurts Reasoning? An Empirical Study on Quantized Reasoning Models
by: Liu, Ruikang, et al.
Published: (2025)

Preserve-Then-Quantize: Balancing Rank Budgets for Quantization Error Reconstruction in LLMs
by: Cho, Yoonjun, et al.
Published: (2026)

BATQuant: Outlier-resilient MXFP4 Quantization via Learnable Block-wise Optimization
by: Li, Ji-Fu, et al.
Published: (2026)

Gradient Based Method for the Fusion of Lattice Quantizers
by: Zhang, Liyuan, et al.
Published: (2025)

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

Continuous Approximations for Improving Quantization Aware Training of LLMs
by: Li, He, et al.
Published: (2024)

LFQ: Logit-aware Final-block Quantization for Boosting the Generation Quality of Low-Bit Quantized LLMs
by: Lee, Jung Hyun, et al.
Published: (2026)

Learning Graph Quantized Tokenizers
by: Wang, Limei, et al.
Published: (2024)

Theory-optimal Quantization Based on Flatness
by: Huang, Xiusheng, et al.
Published: (2026)

Quantize More, Lose Less: Autoregressive Generation from Residually Quantized Speech Representations
by: Han, Yichen, et al.
Published: (2025)

UniQL: Unified Quantization and Low-rank Compression for Adaptive Edge LLMs
by: Chiang, Hung-Yueh, et al.
Published: (2025)

Interpreting the Effects of Quantization on LLMs
by: Singh, Manpreet, et al.
Published: (2025)

LQA: A Lightweight Quantized-Adaptive Framework for Vision-Language Models on the Edge
by: Wang, Xin, et al.
Published: (2026)

Integer Scale: A Free Lunch for Faster Fine-grained Quantization of LLMs
by: Li, Qingyuan, et al.
Published: (2024)

QKVShare: Quantized KV-Cache Handoff for Multi-Agent On-Device LLMs
by: Honavar, Pratik, et al.
Published: (2026)

Achieving binary weight and activation for LLMs using Post-Training Quantization
by: Song, Siqing, et al.
Published: (2025)

A Quantized VAE-MLP Botnet Detection Model: A Systematic Evaluation of Quantization-Aware Training and Post-Training Quantization Strategies
by: Wasswa, Hassan, et al.
Published: (2025)

On-the-Fly Adaptation to Quantization: Configuration-Aware LoRA for Efficient Fine-Tuning of Quantized LLMs
by: Ye, Rongguang, et al.
Published: (2025)

Quantized Evolution Strategies: High-precision Fine-tuning of Quantized LLMs at Low-precision Cost
by: Xu, Yinggan, et al.
Published: (2026)

AsymKV: Enabling 1-Bit Quantization of KV Cache with Layer-Wise Asymmetric Quantization Configurations
by: Tao, Qian, et al.
Published: (2024)

Rethinking Generative Recommender Tokenizer: Recsys-Native Encoding and Semantic Quantization Beyond LLMs
by: Liang, Yu, et al.
Published: (2026)

End-to-End On-Device Quantization-Aware Training for LLMs at Inference Cost
by: Tan, Qitao, et al.
Published: (2025)

PatternKV: Flattening KV Representation Expands Quantization Headroom
by: Zhang, Ji, et al.
Published: (2025)

Unveiling the Potential of Quantization with MXFP4: Strategies for Quantization Error Reduction
by: Chhugani, Jatin, et al.
Published: (2026)

Learning under Quantization for High-Dimensional Linear Regression
by: Zhang, Dechen, et al.
Published: (2025)

Multi-Aspect Cross-modal Quantization for Generative Recommendation
by: Zhang, Fuwei, et al.
Published: (2025)

One QuantLLM for ALL: Fine-tuning Quantized LLMs Once for Efficient Deployments
by: Yi, Ke, et al.
Published: (2024)

Channel-wise Vector Quantization
by: Song, Wei, et al.
Published: (2026)