:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Xiao, Shuai, Liu, Su, Zhou, Weikai, Wu, Jialun, He, Xinjie, Lin, Zhiyuan, Xie, Qiyang
Format:	Preprint
Published:	2026
Subjects:	Artificial Intelligence Machine Learning
Online Access:	https://arxiv.org/abs/2605.29420
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

What Training Data Teaches RL Memory Agents: An Empirical Study of Curriculum Effects in Memory-Augmented QA
by: He, Xinjie, et al.
Published: (2026)

Confidence-Gated Robot Autonomy: When Does Uncertainty Actually Help?
by: Gaus, Johannes A., et al.
Published: (2026)

When LLMs Meet API Documentation: Can Retrieval Augmentation Aid Code Generation Just as It Helps Developers?
by: Chen, Jingyi, et al.
Published: (2025)

When Does Sparse MoE Help in Vision? The Role of Backbone Compute Leverage in Sparse Routing
by: Sun, Libo, et al.
Published: (2026)

Soft Attention: Does it Actually Help to Learn Social Interactions in Pedestrian Trajectory Prediction?
by: Boucaud, Laurent, et al.
Published: (2021)

When "A Helpful Assistant" Is Not Really Helpful: Personas in System Prompts Do Not Improve Performances of Large Language Models
by: Zheng, Mingqian, et al.
Published: (2023)

When Does Multi-Agent Collaboration Help? An Entropy Perspective
by: Zhao, Yuxuan, et al.
Published: (2026)

When Do LLMs Need Retrieval Augmentation? Mitigating LLMs' Overconfidence Helps Retrieval Augmentation
by: Ni, Shiyu, et al.
Published: (2024)

The Arrival of AGI? When Expert Personas Exceed Expert Benchmarks
by: Mullens, Drake, et al.
Published: (2026)

SMART: When is it Actually Worth Expanding a Speculative Tree?
by: Wang, Lifu, et al.
Published: (2026)

When Names Disappear: Revealing What LLMs Actually Understand About Code
by: Le, Cuong Chi, et al.
Published: (2025)

Predictive and interactive roles of motivation and situational learning activities on emotional and cognitive engagement
by: Qiyang Lin, et al.
Published: (2026)

Reinforcement Learning with Action Chunking
by: Li, Qiyang, et al.
Published: (2025)

When Does Monolingual Data Help Multilingual Translation: The Role of Domain and Model Scale
by: Baziotis, Christos, et al.
Published: (2023)

When Can LLMs Actually Correct Their Own Mistakes? A Critical Survey of Self-Correction of LLMs
by: Kamoi, Ryo, et al.
Published: (2024)

Analysis of LLMs Against Prompt Injection and Jailbreak Attacks
by: Jaiswal, Piyush, et al.
Published: (2026)

Prompting ChatGPT for Translation: A Comparative Analysis of Translation Brief and Persona Prompts
by: He, Sui
Published: (2024)

Prompt Injection as Role Confusion
by: Ye, Charles, et al.
Published: (2026)

CI w/o TN: Context Injection without Task Name for Procedure Planning
by: Li, Xinjie
Published: (2024)

Automatic and Universal Prompt Injection Attacks against Large Language Models
by: Liu, Xiaogeng, et al.
Published: (2024)

Crafting Customisable Characters with LLMs: A Persona-Driven Role-Playing Agent Framework
by: Yang, Bohao, et al.
Published: (2024)

What Does Loss Optimization Actually Teach, If Anything? Knowledge Dynamics in Continual Pre-training of LLMs
by: Mousavi, Seyed Mahed, et al.
Published: (2026)

Can Persona-Prompted LLMs Emulate Subgroup Values? An Empirical Analysis of Generalisability and Fairness in Cultural Alignment
by: Tan, Bryan Chen Zhengyu, et al.
Published: (2026)

When Do LLMs Help With Node Classification? A Comprehensive Analysis
by: Wu, Xixi, et al.
Published: (2025)

What do Geometric Hallucination Detection Metrics Actually Measure?
by: Yeats, Eric, et al.
Published: (2026)

Fingerprinting LLMs via Prompt Injection
by: Hu, Yuepeng, et al.
Published: (2025)

Not All Queries Need Rewriting: When Prompt-Only LLM Refinement Helps and Hurts Dense Retrieval
by: Kotte, Varun
Published: (2026)

The Code Barrier: What LLMs Actually Understand?
by: Nikiema, Serge Lionel, et al.
Published: (2025)

Enhancing Jailbreak Attacks on LLMs via Persona Prompts
by: Zhang, Zheng, et al.
Published: (2025)

Where Does Long-Context Supervision Actually Go? Effective-Context Exposure Balancing
by: Zhu, Jinchang, et al.
Published: (2026)

When Identity Does Not Help: kinship and migration in the Brazilian context
by: Machado, Igor José de Renó, et al.
Published: (2020)

Temporal Disaggregation of GDP: When Does Machine Learning Help?
by: Jung, Yonggeun
Published: (2025)

Can Emulating Semantic Translation Help LLMs with Code Translation? A Study Based on Pseudocode
by: Chen, Songqiang, et al.
Published: (2025)

Does RAG Know When Retrieval Is Wrong? Diagnosing Context Compliance under Knowledge Conflict
by: Chen, Yihang, et al.
Published: (2026)

Show Me the Infographic I Imagine: Intent-Aware Infographic Retrieval for Authoring Support
by: Xu, Jing, et al.
Published: (2026)

The Vulnerability of LLM Rankers to Prompt Injection Attacks
by: Yin, Yu, et al.
Published: (2026)

ARGUS: Defending Against Multimodal Indirect Prompt Injection via Steering Instruction-Following Behavior
by: Lu, Weikai, et al.
Published: (2025)

PersonaGym: Evaluating Persona Agents and LLMs
by: Samuel, Vinay, et al.
Published: (2024)

Prompt Optimization Is a Coin Flip: Diagnosing When It Helps in Compound AI Systems
by: Zhang, Xing, et al.
Published: (2026)

How Does Knowledge Selection Help Retrieval Augmented Generation?
by: Li, Xiangci, et al.
Published: (2024)