Publications (20)
Reasoning-Based Personalized Generation for Users with Sparse Data
Bo Ni, Branislav Kveton, Samyadeep Basu +14
Large Language Model (LLM) personalization holds great promise for tailoring responses by leveraging personal context and history. However, real-world users usually possess sparse…
Topological design of graphene
Bo Ni, Teng Zhang, Jiaoyan Li +2
Topological defects (e.g. pentagons, heptagons and pentagon-heptagon pairs) have been widely observed in large scale graphene and have been recognized to play important roles in ta…
Compact Turnkey Soliton Microcombs at Microwave Rates via Wafer-Scale Fabrication
Yuanlei Wang, Ze Wang, Chenghao Lao +19
Soliton microcombs generated in nonlinear microresonators facilitate the photonic integration of timing, frequency synthesis, and astronomical calibration functionalities. For thes…
Integrated soliton microcombs beyond the turnkey limit
Ze Wang, Tianyu Xu, Yuanlei Wang +10
Soliton microcombs generated in optical microresonators are accelerating the transition of optical frequency combs from laboratory instruments to industrial platforms. Self injecti…
A Survey on LLM-based Conversational User Simulation
Bo Ni, Leyao Wang, Yu Wang +27
User simulation has long played a vital role in computer science due to its potential to support a wide range of applications. Language, as the primary medium of human communicatio…
Towards Trustworthy Knowledge Graph Reasoning: An Uncertainty Aware Perspective
Bo Ni, Yu Wang, Lu Cheng +2
Recently, Knowledge Graphs (KGs) have been successfully coupled with Large Language Models (LLMs) to mitigate their hallucinations and enhance their reasoning capability, such as i…
Ensemble Privacy Defense for Knowledge-Intensive LLMs against Membership Inference Attacks
Haowei Fu, Bo Ni, Han Xu +3
Retrieval-Augmented Generation (RAG) and Supervised Finetuning (SFT) have become the predominant paradigms for equipping Large Language Models (LLMs) with external knowledge for di…
Towards Bridging Review Sparsity in Recommendation with Textual Edge Graph Representation
Leyao Wang, Xutao Mao, Xuhui Zhan +5
Textual reviews enrich recommender systems with fine-grained preference signals and enhanced explainability. However, in real-world scenarios, users rarely leave reviews, resulting…
Electrically-pumped soliton microcombs on thin-film lithium niobate
Xiaomin Lv, Ze Wang, Tianyu Xu +10
Thin-film lithium niobate (TFLN) has enabled efficient on-chip electro-optic modulation and frequency conversion for information processing and precision measurement. Extending the…
Augmenting Textual Generation via Topology Aware Retrieval
Yu Wang, Nedim Lipka, Ruiyi Zhang +6
Despite the impressive advancements of Large Language Models (LLMs) in generating text, they are often limited by the knowledge contained in the input and prone to producing inaccu…
ForceGen: End-to-end de novo protein generation based on nonlinear mechanical unfolding responses using a protein language diffusion model
Bo Ni, David L. Kaplan, Markus J. Buehler
Through evolution, nature has presented a set of remarkable protein materials, including elastins, silks, keratins and collagens with superior mechanical performances that play cru…
Action Sequence Augmentation for Early Graph-based Anomaly Detection
Tong Zhao, Bo Ni, Wenhao Yu +3
The proliferation of web platforms has created incentives for online abuse. Many graph-based anomaly detection techniques are proposed to identify the suspicious accounts and behav…
Agentic End-to-End De Novo Protein Design for Tailored Dynamics Using a Language Diffusion Model
Bo Ni, Markus J. Buehler
Proteins are dynamic molecular machines whose biological functions, spanning enzymatic catalysis, signal transduction, and structural adaptation, are intrinsically linked to their…
Towards Trustworthy Retrieval Augmented Generation for Large Language Models: A Survey
Bo Ni, Zheyuan Liu, Leyao Wang +17
Retrieval-Augmented Generation (RAG) is an advanced technique designed to address the challenges of Artificial Intelligence-Generated Content (AIGC). By integrating context retriev…
MechAgents: Large language model multi-agent collaborations can solve mechanics problems, generate new data, and integrate knowledge
Bo Ni, Markus J. Buehler
Solving mechanics problems using numerical methods requires comprehensive intelligent capability of retrieving relevant knowledge and theory, constructing and executing codes, anal…
Improving Generalizability of Fake News Detection Methods using Propensity Score Matching
Bo Ni, Zhichun Guo, Jianing Li +1
Recently, due to the booming influence of online social networks, detecting fake news is drawing significant attention from both academic communities and general public. In this pa…
Human-Aligned MLLM Judges for Fine-Grained Image Editing Evaluation: A Benchmark, Framework, and Analysis
Runzhou Liu, Hailey Weingord, Sejal Mittal +18
Evaluating image editing models remains challenging due to the coarse granularity and limited interpretability of traditional metrics, which often fail to capture aspects important…
SaVe-TAG: LLM-based Interpolation for Long-Tailed Text-Attributed Graphs
Leyao Wang, Yu Wang, Bo Ni +4
Real-world graph data often follows long-tailed distributions, making it difficult for Graph Neural Networks (GNNs) to generalize well across both head and tail classes. Recent adv…
Sparse Personalized Text Generation with Multi-Trajectory Reasoning
Bo Ni, Haowei Fu, Qinwen Ge +10
As Large Language Models (LLMs) advance, personalization has become a key mechanism for tailoring outputs to individual user needs. However, most existing methods rely heavily on d…
A Personalized Conversational Benchmark: Towards Simulating Personalized Conversations
Li Li, Peilin Cai, Ryan A. Rossi +21
We present PersonaConvBench, a large-scale benchmark for evaluating personalized reasoning and generation in multi-turn conversations with large language models (LLMs). Unlike exis…