1 citations · 1 across the 8 of their papers we have counts for
8 papers
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…
MRMR: A Realistic and Expert-Level Multidisciplinary Benchmark for Reasoning-Intensive Multimodal Retrieval
Siyue Zhang, Yuan Gao, Xiao Zhou +5
We introduce MRMR, the first expert-level multidisciplinary multimodal retrieval benchmark requiring intensive reasoning. MRMR contains 1,502 queries spanning 23 domains, with posi…
Diffusion vs. Autoregressive Language Models: A Text Embedding Perspective
Siyue Zhang, Yilun Zhao, Liyuan Geng +3
Large language model (LLM)-based embedding models, benefiting from large scale pre-training and post-training, have begun to surpass BERT and T5-based models on general-purpose tex…
SynTQA: Synergistic Table-based Question Answering via Mixture of Text-to-SQL and E2E TQA
Siyue Zhang, Anh Tuan Luu, Chen Zhao
Text-to-SQL parsing and end-to-end question answering (E2E TQA) are two main approaches for Table-based Question Answering task. Despite success on multiple benchmarks, they have y…
Re-Examining Calibration: The Case of Question Answering
Chenglei Si, Chen Zhao, Sewon Min +1
For users to trust model predictions, they need to understand model outputs, particularly their confidence - calibration aims to adjust (calibrate) models' confidence to match expe…