activity
20242026
most citedMMInA: Benchmarking Multihop Multimodal Internet Agents

1 citations · 1 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2026

MoPLEx: Estimating Plackett-Luce Mixture Models for Multi-Objective Alignment

Dongyue Li, Ziniu Zhang, Lu Wang +1

We study learning a mixture of Plackett-Luce models from multi-way ranking responses from annotators that may represent heterogeneous underlying preferences. This problem has m…

cs.LG2025

Learning Multimodal Embeddings for Traffic Accident Prediction and Causal Estimation

Ziniu Zhang, Minxuan Duan, Haris N. Koutsopoulos +1

We consider analyzing traffic accident patterns using both road network data and satellite images aligned to road graph nodes. Previous work for predicting accident occurrences rel…

cs.LG2025

Linear-Time Demonstration Selection for In-Context Learning via Gradient Estimation

Ziniu Zhang, Zhenshuo Zhang, Dongyue Li +3

This paper introduces an algorithm to select demonstration examples for in-context learning of a query set. Given a set of examples, how can we quickly select out of to…

cs.LG2025

Efficient Ensemble for Fine-tuning Language Models on Multiple Datasets

Dongyue Li, Ziniu Zhang, Lu Wang +1

This paper develops an ensemble method for fine-tuning a language model to multiple datasets. Existing methods, such as quantized LoRA (QLoRA), are efficient when adapting to a sin…

cs.CL2024

Scalable Fine-tuning from Multiple Data Sources: A First-Order Approximation Approach

Dongyue Li, Ziniu Zhang, Lu Wang +1

We study the problem of fine-tuning a language model (LM) for a target task by optimally using the information from auxiliary tasks. This problem has broad applications in NLP,…

cs.CV20241 cited

MMInA: Benchmarking Multihop Multimodal Internet Agents

Shulin Tian, Ziniu Zhang, Liangyu Chen +1

Autonomous embodied agents live on an Internet of multimedia websites. Can they hop around multimodal websites to complete complex user tasks? Existing benchmarks fail to assess th…