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From "Weak" Signals to Strong Models: Preference Delta Aggregation with LoRA Merging
Qi Sun, Siyue Zhang, Yulin Chen +3
Training strong large language models (LLMs) requires high-quality supervision, which is often scarce. Recent work shows that paired preference data from weak-weaker model pairs (e…
Rethinking Reasoning-Intensive Retrieval: Evaluating and Advancing Retrievers in Agentic Search Systems
Yilun Zhao, Jinbiao Wei, Tingyu Song +3
Reasoning-intensive retrieval aims to surface evidence that supports downstream reasoning rather than merely matching topical similarity. This capability is increasingly important…
RPDR: A Round-trip Prediction-Based Data Augmentation Framework for Long-Tail Question Answering
Yiming Zhang, Siyue Zhang, Junbo Zhao +1
Long-tail question answering presents significant challenges for large language models (LLMs) due to their limited ability to acquire and accurately recall less common knowledge. R…
Analyzing Diffusion and Autoregressive Vision Language Models in Multimodal Embedding Space
Zihang Wang, Siyue Zhang, Yilun Zhao +4
Embedding models are a fundamental component of modern AI systems such as semantic search and retrieval-augmented generation. Recent advances in large foundation models have substa…