1 citations · 1 across the 6 of their papers we have counts for
9 papers
DocPilot: Interactive Agent Orchestration and Training for Long Visual Document Understanding
Zhuowen Liang, Xiaotian Lin, Yuyu Luo +2
Multimodal long-document question answering requires models to seek sparse evidence across pages and modalities, understand heterogeneous document content, and reason over the coll…
MassAlloc Attention: Let Attention Allocate Its Own Compute
Jingze Shi, Zhangyang Peng, Xianduo Li +6
FullAttn often assigns negligible normalized mass to much of the causal score space, yet dense kernels execute the complete post-score path after forming each QK tile. We introduce…
CoWindow Attention: Full Causal Coverage Is a Collective Property
Jingze Shi, Zhangyang Peng, Xianduo Li +6
FullAttn repeatedly exposes the complete causal history to every attention head, creating substantial redundant computation and memory traffic even with IO-efficient dense kernels.…
DataSpace: Benchmarking Data Agents for Verifiable Analytics over Heterogeneous Workspaces
Boyan Li, Zhuowen Liang, Yupeng Xie +11
Data agents enable natural-language analytics over organizational workspaces, where relevant evidence may be scattered across databases, structured files, long documents, and multi…
TuneAhead: Predicting Fine-tuning Performance Before Full Training Begins
Yuxiang Luo, Haonan Long, Chen Wang +6
Fine-tuning large language models (LLMs) is compute-intensive and error-prone: model performance depends sensitively on data quality and hyperparameter choices, and naïve runs can…
Long-Document QA with Chain-of-Structured-Thought and Fine-Tuned SLMs
Zhuowen Liang, Xiaotian Lin, Zhengxuan Zhang +3
Large language models (LLMs) are widely applied to data analytics over documents, yet direct reasoning over long, noisy documents remains brittle and error-prone. Hence, we study d…
A Survey of Data Agents: Emerging Paradigm or Overstated Hype?
Yizhang Zhu, Liangwei Wang, Chenyu Yang +22
The rapid advancement of large language models (LLMs) has spurred the emergence of data agents, autonomous systems designed to orchestrate Data + AI ecosystems for tackling complex…
Concise Reasoning, Big Gains: Pruning Long Reasoning Trace with Difficulty-Aware Prompting
Yifan Wu, Jingze Shi, Bingheng Wu +4
Existing chain-of-thought (CoT) distillation methods can effectively transfer reasoning abilities to base models but suffer from two major limitations: excessive verbosity of reaso…
LEAD: Iterative Data Selection for Efficient LLM Instruction Tuning
Xiaotian Lin, Yanlin Qi, Yizhang Zhu +4
Instruction tuning has emerged as a critical paradigm for improving the capabilities and alignment of large language models (LLMs). However, existing iterative model-aware data sel…