2 citations · 4 across the 9 of their papers we have counts for
10 papers
FutureX-Pro: Extending Future Prediction to High-Value Vertical Domains
Jiashuo Liu, Siyuan Chen, Zaiyuan Wang +38
Building upon FutureX, which established a live benchmark for general-purpose future prediction, this report introduces FutureX-Pro, including FutureX-Finance, FutureX-Retail, Futu…
Exploiting the Final Component of Generator Architectures for AI-Generated Image Detection
Yanzhu Liu, Xiao Liu, Yuexuan Wang +1
With the rapid proliferation of powerful image generators, accurate detection of AI-generated images has become essential for maintaining a trustworthy online environment. However,…
BMGQ: A Bottom-up Method for Generating Complex Multi-hop Reasoning Questions from Semi-structured Data
Bingsen Qiu, Zijian Liu, Xiao Liu +6
Building training-ready multi-hop question answering (QA) datasets that truly stress a model's retrieval and reasoning abilities remains highly challenging recently. While there ha…
CFVBench: A Comprehensive Video Benchmark for Fine-grained Multimodal Retrieval-Augmented Generation
Kaiwen Wei, Xiao Liu, Jie Zhang +11
Multimodal Retrieval-Augmented Generation (MRAG) enables Multimodal Large Language Models (MLLMs) to generate responses with external multimodal evidence, and numerous video-based…
Seed1.5-VL Technical Report
Dong Guo, Faming Wu, Feida Zhu +194
We present Seed1.5-VL, a vision-language foundation model designed to advance general-purpose multimodal understanding and reasoning. Seed1.5-VL is composed with a 532M-parameter v…
QUDSELECT: Selective Decoding for Questions Under Discussion Parsing
Ashima Suvarna, Xiao Liu, Tanmay Parekh +2
Question Under Discussion (QUD) is a discourse framework that uses implicit questions to reveal discourse relationships between sentences. In QUD parsing, each sentence is viewed a…
Attribute or Abstain: Large Language Models as Long Document Assistants
Jan Buchmann, Xiao Liu, Iryna Gurevych
LLMs can help humans working with long documents, but are known to hallucinate. Attribution can increase trust in LLM responses: The LLM provides evidence that supports its respons…
External Prompt Features Enhanced Parameter-efficient Fine-tuning for Salient Object Detection
Wen Liang, Peipei Ran, Mengchao Bai +4
Salient object detection (SOD) aims at finding the most salient objects in images and outputs pixel-level binary masks. Transformer-based methods achieve promising performance due…
Crimson: Empowering Strategic Reasoning in Cybersecurity through Large Language Models
Jiandong Jin, Bowen Tang, Mingxuan Ma +5
We introduces Crimson, a system that enhances the strategic reasoning capabilities of Large Language Models (LLMs) within the realm of cybersecurity. By correlating CVEs with MITRE…
SeqDialN: Sequential Visual Dialog Networks in Joint Visual-Linguistic Representation Space
Liu Yang
In this work, we formulate a visual dialog as an information flow in which each piece of information is encoded with the joint visual-linguistic representation of a single dialog r…