Understanding the Ability of LLMs to Handle Character-Level Perturbation
Fuente:
arXiv
Saved in:
| Main Authors: | Zhuo, Anyuan, Ning, Xuefei, Li, Ningyuan, Zhu, Jingyi, Wang, Yu, Lu, Pinyan |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Enhancing Character-Level Understanding in LLMs through Token Internal Structure Learning
by: Xu, Zhu, et al.
Published: (2024)
by: Xu, Zhu, et al.
Published: (2024)
MATH-Perturb: Benchmarking LLMs' Math Reasoning Abilities against Hard Perturbations
by: Huang, Kaixuan, et al.
Published: (2025)
by: Huang, Kaixuan, et al.
Published: (2025)
Exposing the Achilles' Heel: Evaluating LLMs Ability to Handle Mistakes in Mathematical Reasoning
by: Singh, Joykirat, et al.
Published: (2024)
by: Singh, Joykirat, et al.
Published: (2024)
Rethinking the Understanding Ability across LLMs through Mutual Information
by: Wang, Shaojie, et al.
Published: (2025)
by: Wang, Shaojie, et al.
Published: (2025)
ZPD-SCA: Unveiling the Blind Spots of LLMs in Assessing Students' Cognitive Abilities
by: Dong, Wenhan, et al.
Published: (2025)
by: Dong, Wenhan, et al.
Published: (2025)
Teaching Human Behavior Improves Content Understanding Abilities Of LLMs
by: Singh, Somesh, et al.
Published: (2024)
by: Singh, Somesh, et al.
Published: (2024)
Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation
by: Ning, Xuefei, et al.
Published: (2023)
by: Ning, Xuefei, et al.
Published: (2023)
Single Character Perturbations Break LLM Alignment
by: Lin, Leon, et al.
Published: (2024)
by: Lin, Leon, et al.
Published: (2024)
OpenCharacter: Training Customizable Role-Playing LLMs with Large-Scale Synthetic Personas
by: Wang, Xiaoyang, et al.
Published: (2025)
by: Wang, Xiaoyang, et al.
Published: (2025)
A Survey on Enhancing Causal Reasoning Ability of Large Language Models
by: Li, Xin, et al.
Published: (2025)
by: Li, Xin, et al.
Published: (2025)
How Well Do LLMs Handle Cantonese? Benchmarking Cantonese Capabilities of Large Language Models
by: Jiang, Jiyue, et al.
Published: (2024)
by: Jiang, Jiyue, et al.
Published: (2024)
Atomic Thinking of LLMs: Decoupling and Exploring Mathematical Reasoning Abilities
by: Kuang, Jiayi, et al.
Published: (2025)
by: Kuang, Jiayi, et al.
Published: (2025)
Evaluating Character Understanding of Large Language Models via Character Profiling from Fictional Works
by: Yuan, Xinfeng, et al.
Published: (2024)
by: Yuan, Xinfeng, et al.
Published: (2024)
The Essence of Contextual Understanding in Theory of Mind: A Study on Question Answering with Story Characters
by: Zhou, Chulun, et al.
Published: (2025)
by: Zhou, Chulun, et al.
Published: (2025)
Enhancing the Medical Context-Awareness Ability of LLMs via Multifaceted Self-Refinement Learning
by: Zhou, Yuxuan, et al.
Published: (2025)
by: Zhou, Yuxuan, et al.
Published: (2025)
Few-Shot Character Understanding in Movies as an Assessment to Meta-Learning of Theory-of-Mind
by: Yu, Mo, et al.
Published: (2022)
by: Yu, Mo, et al.
Published: (2022)
Code Prompting Elicits Conditional Reasoning Abilities in Text+Code LLMs
by: Puerto, Haritz, et al.
Published: (2024)
by: Puerto, Haritz, et al.
Published: (2024)
LLM-CAS: Dynamic Neuron Perturbation for Real-Time Hallucination Correction
by: Zhang, Jensen, et al.
Published: (2025)
by: Zhang, Jensen, et al.
Published: (2025)
FlashVTG: Feature Layering and Adaptive Score Handling Network for Video Temporal Grounding
by: Cao, Zhuo, et al.
Published: (2024)
by: Cao, Zhuo, et al.
Published: (2024)
Do LLMs Have the Generalization Ability in Conducting Causal Inference?
by: Wang, Chen, et al.
Published: (2024)
by: Wang, Chen, et al.
Published: (2024)
The Impact of Visual Information in Chinese Characters: Evaluating Large Models' Ability to Recognize and Utilize Radicals
by: Wu, Xiaofeng, et al.
Published: (2024)
by: Wu, Xiaofeng, et al.
Published: (2024)
Memorization $\neq$ Understanding: Do Large Language Models Have the Ability of Scenario Cognition?
by: Ma, Boxiang, et al.
Published: (2025)
by: Ma, Boxiang, et al.
Published: (2025)
TactfulToM: Do LLMs Have the Theory of Mind Ability to Understand White Lies?
by: Liu, Yiwei, et al.
Published: (2025)
by: Liu, Yiwei, et al.
Published: (2025)
Enhancing LLM Character-Level Manipulation via Divide and Conquer
by: Xiong, Zhen, et al.
Published: (2025)
by: Xiong, Zhen, et al.
Published: (2025)
Improve LLM-as-a-Judge Ability as a General Ability
by: Yu, Jiachen, et al.
Published: (2025)
by: Yu, Jiachen, et al.
Published: (2025)
ProSA: Assessing and Understanding the Prompt Sensitivity of LLMs
by: Zhuo, Jingming, et al.
Published: (2024)
by: Zhuo, Jingming, et al.
Published: (2024)
Show, Don't Tell: Uncovering Implicit Character Portrayal using LLMs
by: Jaipersaud, Brandon, et al.
Published: (2024)
by: Jaipersaud, Brandon, et al.
Published: (2024)
SpeLLM: Character-Level Multi-Head Decoding
by: Ben-Artzy, Amit, et al.
Published: (2025)
by: Ben-Artzy, Amit, et al.
Published: (2025)
Exact Hard Monotonic Attention for Character-Level Transduction
by: Wu, Shijie, et al.
Published: (2019)
by: Wu, Shijie, et al.
Published: (2019)
Cross-lingual, Character-Level Neural Morphological Tagging
by: Cotterell, Ryan, et al.
Published: (2017)
by: Cotterell, Ryan, et al.
Published: (2017)
Hard Non-Monotonic Attention for Character-Level Transduction
by: Wu, Shijie, et al.
Published: (2018)
by: Wu, Shijie, et al.
Published: (2018)
ScholarSearch: Benchmarking Scholar Searching Ability of LLMs
by: Zhou, Junting, et al.
Published: (2025)
by: Zhou, Junting, et al.
Published: (2025)
Olapa-MCoT: Enhancing the Chinese Mathematical Reasoning Capability of LLMs
by: Zhu, Shaojie, et al.
Published: (2023)
by: Zhu, Shaojie, et al.
Published: (2023)
CHATTER: A Character Attribution Dataset for Narrative Understanding
by: Baruah, Sabyasachee, et al.
Published: (2024)
by: Baruah, Sabyasachee, et al.
Published: (2024)
Word Recovery in Large Language Models Enables Character-Level Tokenization Robustness
by: Yang, Zhipeng, et al.
Published: (2026)
by: Yang, Zhipeng, et al.
Published: (2026)
Character-Level Chinese Dependency Parsing via Modeling Latent Intra-Word Structure
by: Hou, Yang, et al.
Published: (2024)
by: Hou, Yang, et al.
Published: (2024)
Quantifying the Reasoning Abilities of LLMs on Real-world Clinical Cases
by: Qiu, Pengcheng, et al.
Published: (2025)
by: Qiu, Pengcheng, et al.
Published: (2025)
Thunder-NUBench: A Benchmark for LLMs' Sentence-Level Negation Understanding
by: So, Yeonkyoung, et al.
Published: (2025)
by: So, Yeonkyoung, et al.
Published: (2025)
Shadows in the Attention: Contextual Perturbation and Representation Drift in the Dynamics of Hallucination in LLMs
by: Wei, Zeyu, et al.
Published: (2025)
by: Wei, Zeyu, et al.
Published: (2025)
SeqAR: Jailbreak LLMs with Sequential Auto-Generated Characters
by: Yang, Yan, et al.
Published: (2024)
by: Yang, Yan, et al.
Published: (2024)
Similar Items
-
Enhancing Character-Level Understanding in LLMs through Token Internal Structure Learning
by: Xu, Zhu, et al.
Published: (2024) -
MATH-Perturb: Benchmarking LLMs' Math Reasoning Abilities against Hard Perturbations
by: Huang, Kaixuan, et al.
Published: (2025) -
Exposing the Achilles' Heel: Evaluating LLMs Ability to Handle Mistakes in Mathematical Reasoning
by: Singh, Joykirat, et al.
Published: (2024) -
Rethinking the Understanding Ability across LLMs through Mutual Information
by: Wang, Shaojie, et al.
Published: (2025) -
ZPD-SCA: Unveiling the Blind Spots of LLMs in Assessing Students' Cognitive Abilities
by: Dong, Wenhan, et al.
Published: (2025)