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Works60 from public data
- Qwen2 Technical Report2,548
A comprehensive suite of foundational and instruction-tuned language models, encompassing a parameter range from 0.5 to 72 billion, featuring dense models and a Mixture-of-Experts model, which surpasses most prior open-weight models and demonstrates robust multilingual capabilities.
- Logic-Driven Context Extension and Data Augmentation for Logical Reasoning of Text94
The results show that the proposed logic-driven data augmentation algorithm achieves state-of-the-art performance on both datasets, and even surpasses human performance on the ReClor dataset.
- Mask Attention Networks: Rethinking and Strengthen Transformer83
A novel understanding of SAN and FFN are presented as Mask Attention Networks (MANs) and it is shown that they are two special cases of MANs with static mask matrices, which limit the capability for localness modeling in text representation learning.
- An Online Mammography Database with Biopsy Confirmed Types69
A database containing two online breast mammographies to enrich the diversity of mammography data and promote the development of relevant fields is constructed.
- A Question Type Driven Framework to Diversify Visual Question Generation58
A question type driven framework to produce multiple questions for a given image with different focuses is proposed, which outperforms the state-of-the-art approaches in terms of both relevance and diversity.
- A Reinforcement Learning Framework for Natural Question Generation using Bi-discriminators51
This work argues that natural questions need to have two specific attributes from the perspectives of content and linguistic respectively, namely, natural and human-written, and proposes two discriminators, one for each attribute, to enhance the training.
- A Multi-Agent Communication Framework for Question-Worthy Phrase Extraction and Question Generation46
A multi-agent communication framework is introduced, taking phrase extraction and question generation as two agents, and learn these two tasks simultaneously via message passing mechanism and can extract question-worthy phrases, which are able to improve the performance of question generation.
- An Enhanced Knowledge Injection Model for Commonsense Generation32
This work integrates two additional modules into the pretrained encoder-decoder model for prototype modeling to enhance the knowledge injection procedure and shows results that significantly improves the performance on all the metrics.
- TCIC: Theme Concepts Learning Cross Language and Vision for Image Captioning30
A Theme Concepts extended Image Captioning (TCIC) framework that incorporates theme concepts to represent high-level cross-modality semantics is proposed and experimental results on MS COCO show the effectiveness of the approach compared to some state-of-the-art models.
- Bridging by Word: Image Grounded Vocabulary Construction for Visual Captioning27
A novel hierarchical structure is proposed to construct an image-grounded vocabulary, based on which, captions are generated with limitation and guidance, and the effectiveness of this framework compared to some state-of-the-art models is shown.
- MVPTR26
This paper proposes to learn Multi-level semantic alignment for Vision-language Pre-TRaining (MVPTR), a nested structure of both modalities to introduce concepts as high-level semantics and achieves state-of-the-art results on several vision and language tasks.
- Unifying Cross-Lingual and Cross-Modal Modeling Towards Weakly Supervised Multilingual Vision-Language Pre-training22
It is argued that the universal multilingual representation learned from texts allows the cross-modal interaction learned in English to be transferable to other languages, and a framework to effectively unify cross-lingual and cross- modal pre-training is proposed.
- PathQG: Neural Question Generation from Facts22
This paper presents a novel task of question generation given a query path in the knowledge graph constructed from the input text, and formulate query representation learning as a sequence labeling problem for identifying the involved facts to form a query and employ an RNN-based generator for question generation.
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- ReForm-Eval: Evaluating Large Vision Language Models via Unified Re-Formulation of Task-Oriented Benchmarks17
This work proposes to re-formulate existing benchmarks into unified LVLM-compatible formats and presents ReForm-Eval benchmark, offering substantial data for evaluating various capabilities of LVLMs, demonstrating the comprehensiveness and reliability of ReForm-Eval in assessing various LVLMs.
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- Constructing Phrase-level Semantic Labels to Form Multi-Grained Supervision for Image-Text Retrieval13
- Locate Then Ask: Interpretable Stepwise Reasoning for Multi-hop Question Answering11
This paper proposes an interpretable stepwise reasoning framework to incorporate both single-hop supporting sentence identification and single-Hop question generation at each intermediate step, and utilize the inference of the current hop for the next until reasoning out the final result.
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- MIPI 2024 Challenge on Demosaic for Hybridevs Camera: Methods and Results9
A total of 110 participants from both industrial and academic backgrounds contributed many valuable solutions to address the difficulty of the restoration of HybridEVS’s raw data, thus raising the reconstructed performance to a new height.
Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-13. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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