activity
20232026
most citedGalleryGPT: Analyzing Paintings with Large Multimodal Models

33 citations · 41 across the 13 of their papers we have counts for

collaborators

13 papers

cs.LG2026

ThinkTank-ME: A Multi-Expert Framework for Middle East Event Forecasting

Haoxuan Li, He Chang, Yunshan Ma +4

Event forecasting is inherently influenced by multifaceted considerations, including international relations, regional historical dynamics, and cultural contexts. However, existing…

cs.CV2025

HarmoCLIP: Harmonizing Global and Regional Representations in Contrastive Vision-Language Models

Haoxi Zeng, Haoxuan Li, Yi Bin +4

Contrastive Language-Image Pre-training (CLIP) has demonstrated remarkable generalization ability and strong performance across a wide range of vision-language tasks. However, due…

cs.CL2025

More Than One Teacher: Adaptive Multi-Guidance Policy Optimization for Diverse Exploration

Xiaoyang Yuan, Yujuan Ding, Yi Bin +5

Reinforcement Learning with Verifiable Rewards (RLVR) is a promising paradigm for enhancing the reasoning ability in Large Language Models (LLMs). However, prevailing methods prima…

cs.CV2025

GeoPurify: A Data-Efficient Geometric Distillation Framework for Open-Vocabulary 3D Segmentation

Weijia Dou, Xu Zhang, Yi Bin +5

Recent attempts to transfer features from 2D Vision-Language Models (VLMs) to 3D semantic segmentation expose a persistent trade-off. Directly projecting 2D features into 3D yields…

cs.CL2025

Multimodal Mathematical Reasoning with Diverse Solving Perspective

Wenhao Shi, Zhiqiang Hu, Yi Bin +4

Recent progress in large-scale reinforcement learning (RL) has notably enhanced the reasoning capabilities of large language models (LLMs), especially in mathematical domains. Howe…

cs.IR2025

SemCORE: A Semantic-Enhanced Generative Cross-Modal Retrieval Framework with MLLMs

Haoxuan Li, Yi Bin, Yunshan Ma +4

Cross-modal retrieval (CMR) is a fundamental task in multimedia research, focused on retrieving semantically relevant targets across different modalities. While traditional CMR met…

cs.MM2024★ 4 cited

MM-Forecast: A Multimodal Approach to Temporal Event Forecasting with Large Language Models

Haoxuan Li, Zhengmao Yang, Yunshan Ma +3

We study an emerging and intriguing problem of multimodal temporal event forecasting with large language models. Compared to using text or graph modalities, the investigation of ut…

cs.CL2024★ 33 cited

GalleryGPT: Analyzing Paintings with Large Multimodal Models

Yi Bin, Wenhao Shi, Yujuan Ding +5

Artwork analysis is important and fundamental skill for art appreciation, which could enrich personal aesthetic sensibility and facilitate the critical thinking ability. Understand…

cs.MM2024★ 2 cited

Leveraging Weak Cross-Modal Guidance for Coherence Modelling via Iterative Learning

Yi Bin, Junrong Liao, Yujuan Ding +4

Cross-modal coherence modeling is essential for intelligent systems to help them organize and structure information, thereby understanding and creating content of the physical worl…

cs.CL2024

Math-LLaVA: Bootstrapping Mathematical Reasoning for Multimodal Large Language Models

Wenhao Shi, Zhiqiang Hu, Yi Bin +5

Large language models (LLMs) have demonstrated impressive reasoning capabilities, particularly in textual mathematical problem-solving. However, existing open-source image instruct…

cs.CL2023★ 1 cited

Solving Math Word Problems with Reexamination

Yi Bin, Wenhao Shi, Yujuan Ding +2

Math word problem (MWP) solving aims to understand the descriptive math problem and calculate the result, for which previous efforts are mostly devoted to upgrade different technic…

cs.SI2023★ 1 cited

Cross-modal Consistency Learning with Fine-grained Fusion Network for Multimodal Fake News Detection

Jun Li, Yi Bin, Jie Zou +2

Previous studies on multimodal fake news detection have observed the mismatch between text and images in the fake news and attempted to explore the consistency of multimodal news b…

cs.CL2023

Non-Autoregressive Sentence Ordering

Yi Bin, Wenhao Shi, Bin Ji +3

Existing sentence ordering approaches generally employ encoder-decoder frameworks with the pointer net to recover the coherence by recurrently predicting each sentence step-by-step…