1 citations · 1 across the 9 of their papers we have counts for
10 papers
CORE: Improving Compositional Reasoning in MLLM Embedding via Reranker Distillation
Tingyu Song, Mingxin Li, Yanzhao Zhang +5
MLLM-based embedding models remain limited in compositional retrieval, often failing to distinguish scenes containing the same concepts but different attribute-object bindings. Yet…
UEmbed: Unified Sparse and Dense Multimodal Embeddings
Tingyu Song, Mingxin Li, Yanzhao Zhang +5
Sparse retrieval underpins modern search systems, from web search to retrieval-augmented generation. Existing work has introduced Learned Sparse Retrieval (LSR) to push beyond exac…
An evidence-guided reinforcement learning method to improve psychiatric reasoning in small language models
Xinxin Lin, Guangxin Dai, Yi Zhong +25
Privacy and computational constraints limit the use of large language models in psychiatry, while adapting small language models (SLMs) often requires substantial data and expert a…
Rethinking Composed Image Retrieval Evaluation: A Fine-Grained Benchmark from Image Editing
Tingyu Song, Yanzhao Zhang, Mingxin Li +6
Composed Image Retrieval (CIR) is a pivotal and complex task in multimodal understanding. Current CIR benchmarks typically feature limited query categories and fail to capture the…
From Deferral to Learning: Online In-Context Knowledge Distillation for LLM Cascades
Yu Wu, Shuo Wu, Ye Tao +2
Standard LLM cascades improve efficiency by deferring difficult queries from weak to strong models. However, these systems are typically static: when faced with repeated or semanti…
LLM Unlearning Should Be Form-Independent
Xiaotian Ye, Mengqi Zhang, Shu Wu
Large Language Model (LLM) unlearning aims to erase or suppress undesirable knowledge within the model, offering promise for controlling harmful or private information to prevent m…
Multi-MLLM Knowledge Distillation for Out-of-Context News Detection
Yimeng Gu, Zhao Tong, Ignacio Castro +2
Multimodal out-of-context news is a type of misinformation in which the image is used outside of its original context. Many existing works have leveraged multimodal large language…
Open Problems and a Hypothetical Path Forward in LLM Knowledge Paradigms
Xiaotian Ye, Mengqi Zhang, Shu Wu
Knowledge is fundamental to the overall capabilities of Large Language Models (LLMs). The knowledge paradigm of a model, which dictates how it encodes and utilizes knowledge, signi…
Tuning LLMs by RAG Principles: Towards LLM-native Memory
Jiale Wei, Shuchi Wu, Ruochen Liu +3
Memory, additional information beyond the training of large language models (LLMs), is crucial to various real-world applications, such as personal assistant. The two mainstream so…
Learning Domain-Invariant Features for Out-of-Context News Detection
Yimeng Gu, Mengqi Zhang, Ignacio Castro +2
Out-of-context news is a common type of misinformation on online media platforms. This involves posting a caption, alongside a mismatched news image. Existing out-of-context news d…