3 citations · 5 across the 8 of their papers we have counts for
8 papers
BOUND: Brief-Guided Corrective Preference Distillation at Search-Control Boundaries
Qingying Niu, Ruiyang Ren, Wayne Xin Zhao +1
Large language model (LLM)-based deep search agents solve tasks through iterative retrieval and reasoning, but locally relevant evidence can cause persistent wrong-anchor drift, co…
Leveraging LLM-based agents for social science research: insights from citation network simulations
Jiarui Ji, Runlin Lei, Xuchen Pan +8
The emergence of Large Language Models (LLMs) demonstrates their potential to encapsulate the logic and patterns inherent in human behavior simulation by leveraging extensive web d…
PAL-UI: Planning with Active Look-back for Vision-Based GUI Agents
Zikang Liu, Junyi Li, Wayne Xin Zhao +3
Graphical User Interface (GUI) agents powered by Multimodal Large Language Models (MLLMs) promise human-like interaction with software applications, yet long-horizon tasks remain c…
Do we Really Need Visual Instructions? Towards Visual Instruction-Free Fine-tuning for Large Vision-Language Models
Zikang Liu, Kun Zhou, Wayne Xin Zhao +3
Visual instruction tuning has become the predominant technology in eliciting the multimodal task-solving capabilities of large vision-language models (LVLMs). Despite the success,…
GenSim: A General Social Simulation Platform with Large Language Model based Agents
Jiakai Tang, Heyang Gao, Xuchen Pan +11
With the rapid advancement of large language models (LLMs), recent years have witnessed many promising studies on leveraging LLM-based agents to simulate human social behavior. Whi…
Unleashing the Potential of Large Language Models as Prompt Optimizers: Analogical Analysis with Gradient-based Model Optimizers
Xinyu Tang, Xiaolei Wang, Wayne Xin Zhao +3
Automatic prompt optimization is an important approach to improving the performance of large language models (LLMs). Recent research demonstrates the potential of using LLMs as pro…
Data-CUBE: Data Curriculum for Instruction-based Sentence Representation Learning
Yingqian Min, Kun Zhou, Dawei Gao +3
Recently, multi-task instruction tuning has been applied into sentence representation learning, which endows the capability of generating specific representations with the guidance…
ReasoningLM: Enabling Structural Subgraph Reasoning in Pre-trained Language Models for Question Answering over Knowledge Graph
Jinhao Jiang, Kun Zhou, Wayne Xin Zhao +2
Question Answering over Knowledge Graph (KGQA) aims to seek answer entities for the natural language question from a large-scale Knowledge Graph~(KG). To better perform reasoning o…