How Far are LLMs from Real Search? A Comprehensive Study on Efficiency, Completeness, and Inherent Capabilities
Fuente:
arXiv
Saved in:
| Main Authors: | Lin, Minhua, Liu, Hui, Tang, Xianfeng, Zeng, Jingying, Dai, Zhenwei, Luo, Chen, Li, Zheng, Zhang, Xiang, He, Qi, Wang, Suhang |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
How Far Are LLMs from Professional Poker Players? Revisiting Game-Theoretic Reasoning with Agentic Tool Use
by: Lin, Minhua, et al.
Published: (2026)
by: Lin, Minhua, et al.
Published: (2026)
A Comprehensive Survey on Reinforcement Learning-based Agentic Search: Foundations, Roles, Optimizations, Evaluations, and Applications
by: Lin, Minhua, et al.
Published: (2025)
by: Lin, Minhua, et al.
Published: (2025)
Bradley-Terry and Multi-Objective Reward Modeling Are Complementary
by: Zhang, Zhiwei, et al.
Published: (2025)
by: Zhang, Zhiwei, et al.
Published: (2025)
Adaptive Test-Time Reasoning via Reward-Guided Dual-Phase Search
by: Cui, Yingqian, et al.
Published: (2025)
by: Cui, Yingqian, et al.
Published: (2025)
Cite Before You Speak: Enhancing Context-Response Grounding in E-commerce Conversational LLM-Agents
by: Zeng, Jingying, et al.
Published: (2025)
by: Zeng, Jingying, et al.
Published: (2025)
AgentTTS: Large Language Model Agent for Test-time Compute-optimal Scaling Strategy in Complex Tasks
by: Wang, Fali, et al.
Published: (2025)
by: Wang, Fali, et al.
Published: (2025)
A Survey of Calibration Process for Black-Box LLMs
by: Xie, Liangru, et al.
Published: (2024)
by: Xie, Liangru, et al.
Published: (2024)
A General Framework to Enhance Fine-tuning-based LLM Unlearning
by: Ren, Jie, et al.
Published: (2025)
by: Ren, Jie, et al.
Published: (2025)
MemMA: Coordinating the Memory Cycle through Multi-Agent Reasoning and In-Situ Self-Evolution
by: Lin, Minhua, et al.
Published: (2026)
by: Lin, Minhua, et al.
Published: (2026)
To trust or not to trust: Attention-based Trust Management for LLM Multi-Agent Systems
by: He, Pengfei, et al.
Published: (2025)
by: He, Pengfei, et al.
Published: (2025)
Position: Agentic Evolution is the Path to Evolving LLMs
by: Lin, Minhua, et al.
Published: (2026)
by: Lin, Minhua, et al.
Published: (2026)
Examples as the Prompt: A Scalable Approach for Efficient LLM Adaptation in E-Commerce
by: Zeng, Jingying, et al.
Published: (2025)
by: Zeng, Jingying, et al.
Published: (2025)
PreGIP: Watermarking the Pretraining of Graph Neural Networks for Deep Intellectual Property Protection
by: Dai, Enyan, et al.
Published: (2024)
by: Dai, Enyan, et al.
Published: (2024)
Stepwise Perplexity-Guided Refinement for Efficient Chain-of-Thought Reasoning in Large Language Models
by: Cui, Yingqian, et al.
Published: (2025)
by: Cui, Yingqian, et al.
Published: (2025)
Keeping an Eye on LLM Unlearning: The Hidden Risk and Remedy
by: Ren, Jie, et al.
Published: (2025)
by: Ren, Jie, et al.
Published: (2025)
Divide-Verify-Refine: Can LLMs Self-Align with Complex Instructions?
by: Zhang, Xianren, et al.
Published: (2024)
by: Zhang, Xianren, et al.
Published: (2024)
Comprehensive Attribution: Inherently Explainable Vision Model with Feature Detector
by: Zhang, Xianren, et al.
Published: (2024)
by: Zhang, Xianren, et al.
Published: (2024)
Rethinking Graph Backdoor Attacks: A Distribution-Preserving Perspective
by: Zhang, Zhiwei, et al.
Published: (2024)
by: Zhang, Zhiwei, et al.
Published: (2024)
Unlocking the Power of Multi-Agent LLM for Reasoning: From Lazy Agents to Deliberation
by: Zhang, Zhiwei, et al.
Published: (2025)
by: Zhang, Zhiwei, et al.
Published: (2025)
Stealing Training Graphs from Graph Neural Networks
by: Lin, Minhua, et al.
Published: (2024)
by: Lin, Minhua, et al.
Published: (2024)
Comprehensive Vulnerability Analysis is Necessary for Trustworthy LLM-MAS
by: He, Pengfei, et al.
Published: (2025)
by: He, Pengfei, et al.
Published: (2025)
LLM and GNN are Complementary: Distilling LLM for Multimodal Graph Learning
by: Xu, Junjie, et al.
Published: (2024)
by: Xu, Junjie, et al.
Published: (2024)
Seeing but Not Believing: Probing the Disconnect Between Visual Attention and Answer Correctness in VLMs
by: Liu, Zhining, et al.
Published: (2025)
by: Liu, Zhining, et al.
Published: (2025)
Are You Using Reliable Graph Prompts? Trojan Prompt Attacks on Graph Neural Networks
by: Lin, Minhua, et al.
Published: (2024)
by: Lin, Minhua, et al.
Published: (2024)
Measuring Emergent Capabilities of LLMs for Software Engineering: How Far Are We?
by: O'Brien, Conor, et al.
Published: (2024)
by: O'Brien, Conor, et al.
Published: (2024)
SUA: Stealthy Multimodal Large Language Model Unlearning Attack
by: Zhang, Xianren, et al.
Published: (2025)
by: Zhang, Xianren, et al.
Published: (2025)
Exploring Query Understanding for Amazon Product Search
by: Luo, Chen, et al.
Published: (2024)
by: Luo, Chen, et al.
Published: (2024)
Robustness Inspired Graph Backdoor Defense
by: Zhang, Zhiwei, et al.
Published: (2024)
by: Zhang, Zhiwei, et al.
Published: (2024)
TRAJECT-Bench:A Trajectory-Aware Benchmark for Evaluating Agentic Tool Use
by: He, Pengfei, et al.
Published: (2025)
by: He, Pengfei, et al.
Published: (2025)
ChartEdit: How Far Are MLLMs From Automating Chart Analysis? Evaluating MLLMs' Capability via Chart Editing
by: Zhao, Xuanle, et al.
Published: (2025)
by: Zhao, Xuanle, et al.
Published: (2025)
Decoding Time Series with LLMs: A Multi-Agent Framework for Cross-Domain Annotation
by: Lin, Minhua, et al.
Published: (2024)
by: Lin, Minhua, et al.
Published: (2024)
WildDoc: How Far Are We from Achieving Comprehensive and Robust Document Understanding in the Wild?
by: Wang, An-Lan, et al.
Published: (2025)
by: Wang, An-Lan, et al.
Published: (2025)
Evaluating the Unseen Capabilities: How Many Theorems Do LLMs Know?
by: Li, Xiang, et al.
Published: (2025)
by: Li, Xiang, et al.
Published: (2025)
A Comprehensive Survey of Small Language Models in the Era of Large Language Models: Techniques, Enhancements, Applications, Collaboration with LLMs, and Trustworthiness
by: Wang, Fali, et al.
Published: (2024)
by: Wang, Fali, et al.
Published: (2024)
LLMs are Bug Replicators: An Empirical Study on LLMs' Capability in Completing Bug-prone Code
by: Guo, Liwei, et al.
Published: (2025)
by: Guo, Liwei, et al.
Published: (2025)
LLMs for Relational Reasoning: How Far are We?
by: Li, Zhiming, et al.
Published: (2024)
by: Li, Zhiming, et al.
Published: (2024)
How Explanations Leak the Decision Logic: Stealing Graph Neural Networks via Explanation Alignment
by: Ma, Bin, et al.
Published: (2025)
by: Ma, Bin, et al.
Published: (2025)
Load‐Bearing Piezoelectric Integrated Device with Inherent Stress Monitoring Capabilities
by: Shumin Lin, et al.
Published: (2025)
by: Shumin Lin, et al.
Published: (2025)
Image Corruption-Inspired Membership Inference Attacks against Large Vision-Language Models
by: Wu, Zongyu, et al.
Published: (2025)
by: Wu, Zongyu, et al.
Published: (2025)
Catastrophic Failure of LLM Unlearning via Quantization
by: Zhang, Zhiwei, et al.
Published: (2024)
by: Zhang, Zhiwei, et al.
Published: (2024)
Similar Items
-
How Far Are LLMs from Professional Poker Players? Revisiting Game-Theoretic Reasoning with Agentic Tool Use
by: Lin, Minhua, et al.
Published: (2026) -
A Comprehensive Survey on Reinforcement Learning-based Agentic Search: Foundations, Roles, Optimizations, Evaluations, and Applications
by: Lin, Minhua, et al.
Published: (2025) -
Bradley-Terry and Multi-Objective Reward Modeling Are Complementary
by: Zhang, Zhiwei, et al.
Published: (2025) -
Adaptive Test-Time Reasoning via Reward-Guided Dual-Phase Search
by: Cui, Yingqian, et al.
Published: (2025) -
Cite Before You Speak: Enhancing Context-Response Grounding in E-commerce Conversational LLM-Agents
by: Zeng, Jingying, et al.
Published: (2025)