4.8k citations · 5.3k across the 18 of their papers we have counts for
18 papers
AdaCoT: Pareto-Optimal Adaptive Chain-of-Thought Triggering via Reinforcement Learning
Chenwei Lou, Zewei Sun, Xinnian Liang +6
Large Language Models (LLMs) have demonstrated remarkable capabilities but often face challenges with tasks requiring sophisticated reasoning. While Chain-of-Thought (CoT) promptin…
Seed1.5-Thinking: Advancing Superb Reasoning Models with Reinforcement Learning
ByteDance Seed, :, Jiaze Chen +267
We introduce Seed1.5-Thinking, capable of reasoning through thinking before responding, resulting in improved performance on a wide range of benchmarks. Seed1.5-Thinking achieves 8…
Risks of AI Scientists: Prioritizing Safeguarding Over Autonomy
Xiangru Tang, Qiao Jin, Kunlun Zhu +10
AI scientists powered by large language models have demonstrated substantial promise in autonomously conducting experiments and facilitating scientific discoveries across various d…
GraphText: Graph Reasoning in Text Space
Jianan Zhao, Le Zhuo, Yikang Shen +5
Large Language Models (LLMs) have gained the ability to assimilate human knowledge and facilitate natural language interactions with both humans and other LLMs. However, despite th…
Collaborative Policy Learning for Open Knowledge Graph Reasoning
Cong Fu, Tong Chen, Meng Qu +2
In recent years, there has been a surge of interests in interpretable graph reasoning methods. However, these models often suffer from limited performance when working on sparse an…
Weakly-supervised Knowledge Graph Alignment with Adversarial Learning
Meng Qu, Jian Tang, Yoshua Bengio
This paper studies aligning knowledge graphs from different sources or languages. Most existing methods train supervised methods for the alignment, which usually require a large nu…