5 papers
When Prompts Become Pixels: Prompt-Region Grounding for Multimodal Reasoning
Yongxin Wang, Ruizhe Zhou, Yueling Tang +4
Multimodal large language models increasingly reason over screenshots and documents where the task itself may be written in pixels. Yet benchmarks usually place questions in text,…
Unifying Token and Span Level Supervisions for Few-Shot Sequence Labeling
Zifeng Cheng, Qingyu Zhou, Zhiwei Jiang +3
Few-shot sequence labeling aims to identify novel classes based on only a few labeled samples. Existing methods solve the data scarcity problem mainly by designing token-level or s…
Finding Similar Exercises in Retrieval Manner
Tongwen Huang, Xihua Li, Chao Yi +2
When students make a mistake in an exercise, they can consolidate it by ``similar exercises'' which have the same concepts, purposes and methods. Commonly, for a certain subject an…
TQ-Net: Mixed Contrastive Representation Learning For Heterogeneous Test Questions
He Zhu, Xihua Li, Xuemin Zhao +2
Recently, more and more people study online for the convenience of access to massive learning materials (e.g. test questions/notes), thus accurately understanding learning material…
DialogUSR: Complex Dialogue Utterance Splitting and Reformulation for Multiple Intent Detection
Haoran Meng, Zheng Xin, Tianyu Liu +6
While interacting with chatbots, users may elicit multiple intents in a single dialogue utterance. Instead of training a dedicated multi-intent detection model, we propose DialogUS…