5 papers
CompanionBench: A Theory-Anchored, Real-World-Grounded Benchmark for AI Emotional Companionship
Yao Liu, Guangjia Chai, Yuming Huang +3
LLM companions are deployed at scale in personally consequential settings, yet poorly evaluated. Existing benchmarks use hand-authored scenarios and prompted simulators, aggregate…
FlipVQA: Scaling Multi-modal Instruction Tuning via Textbook-to-Knowledge Synthesis
Zhen Hao Wong, Jingwen Deng, Yuzhao Wang +6
Textbooks are among the richest repositories of human-verified reasoning knowledge, yet their complex layouts contain multi-column typesetting, cross-page question answer separatio…
GDEPO: Group Dual-dynamic and Equal-right Advantage Policy Optimization with Enhanced Training Data Utilization for Sample-Constrained Reinforcement Learning
Zhengqing Yan, Xinyang Liu, Yi Zhang +7
Automated Theorem Proving (ATP) represents a fundamental challenge in Artificial Intelligence (AI), requiring the construction of machine-verifiable proofs in formal languages such…
DataFlow: An LLM-Driven Framework for Unified Data Preparation and Workflow Automation in the Era of Data-Centric AI
Hao Liang, Xiaochen Ma, Zhou Liu +32
The rapidly growing demand for high-quality data in Large Language Models (LLMs) has intensified the need for scalable, reliable, and semantically rich data preparation pipelines.…
LADY: Linear Attention for Autonomous Driving Efficiency without Transformers
Jihao Huang, Xi Xia, Zhiyuan Li +4
End-to-end autonomous driving has emerged as a promising paradigm. However, state-of-the-art methods rely heavily on Transformer architectures. The inherent quadratic complexity of…