A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
Bingxin Xu, Yuzhang Shang, Emilio Ferrara
BATON improves long-horizon robot manipulation by making subtasks the unit of exploration and adding transition-aware memory, boosting task success by 11.6% over SoTA.
Guancheng Zeng, Xueyi Chen, Jiawang Hu, et al.
Routine is a structured multi-step agent planning framework that significantly improves tool-calling accuracy in enterprise scenarios, boosting GPT-4o from 41.1% to 96.3% and enabling smaller models to approach that performance via fine-tuning.
Anand Shankar, Bikash Chandra Sahana
This paper proposes an ensemble of machine learning approaches (boosting, bagging, stacking) to predict low visibility and dense fog at Patna airport, achieving high reliability for aviation services.
Haolei Xu, Xiaowen Xu, Haiwen Hong, et al.
Relay-OPD improves on-policy distillation by detecting student prefix failures and letting the teacher briefly take over to construct relay trajectories, boosting accuracy and cutting training length by over 50%.
Yuzhong Zhao, Yue Liu, Junpeng Liu, et al.
GMPO improves GRPO stability by replacing arithmetic mean with geometric mean of token rewards, reducing outlier sensitivity and boosting reasoning performance.
Zhi‐Hua Zhou
A comprehensive textbook covering ensemble methods including Boosting, Bagging, Random Forest, and diversity measures.
Robi Polikar
This paper reviews ensemble-based systems in decision making, covering conditions for their superiority over single classifiers, algorithms like bagging and boosting, combination rules, and future applications.
Alexey Natekin, Alois Knoll
This tutorial provides a comprehensive introduction to gradient boosting machines, covering methodology, model complexity, and practical applications.
Jerome H. Friedman
This paper introduces gradient boosting machines, a general paradigm for function estimation via stagewise additive expansions and steepest-descent minimization in function space.
Unknown
OmniParser converts UI screenshots into structured elements, boosting GPT-4V's ability to interact accurately with interfaces.
Unknown
V-STaR iteratively improves LLM reasoning by training a DPO verifier on correct and incorrect solutions, boosting generator and verifier performance.
Yiming Jia, Jiachen Li, Xiang Yue, et al.
MAmmoTH-VL 2 introduces VisualWebInstruct, a method using web search and LLMs to create a large multimodal instruction dataset, boosting VLM reasoning performance.