activity
20222026
most citedTowards Better Document-level Relation Extraction via Iterative Inference

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.IR2026

Benchmarking Real-Time Question Answering via Executable Code Workflows

Wenjie Zhou, Yuan Gao, Xin Zhou +5

Retrieving real-time information is a fundamental capability for search-integrated agents in real-world applications. However, existing benchmarks are predominantly static and ther…

cs.CL2026

Can LLMs Track Their Output Length? A Dynamic Feedback Mechanism for Precise Length Regulation

Meiman Xiao, Ante Wang, Qingguo Hu +5

Precisely controlling the length of generated text is a common requirement in real-world applications. However, despite significant advancements in following human instructions, La…

cs.AI2025

SPAN: Benchmarking and Improving Cross-Calendar Temporal Reasoning of Large Language Models

Zhongjian Miao, Hao Fu, Chen Wei

We introduce SPAN, a cross-calendar temporal reasoning benchmark, which requires LLMs to perform intra-calendar temporal reasoning and inter-calendar temporal conversion. SPAN feat…

cs.CL2024

Efficient k-Nearest-Neighbor Machine Translation with Dynamic Retrieval

Yan Gao, Zhiwei Cao, Zhongjian Miao +4

To achieve non-parametric NMT domain adaptation, -Nearest-Neighbor Machine Translation (NN-MT) constructs an external datastore to store domain-specific translation knowledge…

cs.CL2022★ 1 cited

Towards Better Document-level Relation Extraction via Iterative Inference

Liang Zhang, Jinsong Su, Yidong Chen +4

Document-level relation extraction (RE) aims to extract the relations between entities from the input document that usually containing many difficultly-predicted entity pairs whose…