9 papers
Closing the Indexing-Decoding Gap in Multimodal Generative Retrieval via Prefix Retention Optimization
Yufei Chen, Zihan Wang, Yubao Tang +3
Multimodal generative retrieval formulates multimodal retrieval as discrete identifier generation, eliminating the need for explicit similarity search over external embeddings. Exi…
Unsupervised Continual Clustering via Forward-Backward Knowledge Distillation
Mohammadreza Sadeghi, Sareh Soleimani, Zihan Wang +1
Unsupervised Continual Learning (UCL) aims to enable neural networks to learn sequential tasks without labels or access to past data. A major challenge in this setting is Catastrop…
MEG-RAG: Quantifying Multi-modal Evidence Grounding for Evidence Selection in RAG
Xihang Wang, Zihan Wang, Chengkai Huang +2
Multimodal Retrieval-Augmented Generation (MRAG) addresses key limitations of Multimodal Large Language Models (MLLMs), such as hallucination and outdated knowledge. However, curre…
Learning from Medical Entity Trees: An Entity-Centric Medical Data Engineering Framework for MLLMs
Jianghang Lin, Haihua Yang, Deli Yu +6
Multimodal Large Language Models (MLLMs) have shown transformative potential in medical applications, yet their performance is hindered by conventional data curation strategies tha…
MTRouter: Cost-Aware Multi-Turn LLM Routing with History-Model Joint Embeddings
Yiqun Zhang, Hao Li, Zihan Wang +6
Multi-turn, long-horizon tasks are increasingly common for large language models (LLMs), but solving them typically requires many sequential model invocations, accumulating substan…
ChartNet: A Million-Scale, High-Quality Multimodal Dataset for Robust Chart Understanding
Jovana Kondic, Pengyuan Li, Dhiraj Joshi +24
Understanding charts requires models to jointly reason over geometric visual patterns, structured numerical data, and natural language -- a capability where current vision-language…