Poster "reasoning capabilities" Papers
10 papers found
From Artificial Needles to Real Haystacks: Improving Retrieval Capabilities in LLMs by Finetuning on Synthetic Data
Zheyang Xiong, Vasilis Papageorgiou, Kangwook Lee et al.
ICLR 2025posterarXiv:2406.19292
19
citations
GRIP: A Graph-Based Reasoning Instruction Producer
Jiankang Wang, Jianjun Xu, Xiaorui Wang et al.
NeurIPS 2025posterarXiv:2412.08864
2
citations
Mixture of Parrots: Experts improve memorization more than reasoning
Samy Jelassi, Clara Mohri, David Brandfonbrener et al.
ICLR 2025posterarXiv:2410.19034
14
citations
ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models
Mingjie Liu, Shizhe Diao, Ximing Lu et al.
NeurIPS 2025posterarXiv:2505.24864
99
citations
SynLogic: Synthesizing Verifiable Reasoning Data at Scale for Learning Logical Reasoning and Beyond
Junteng Liu, Yuanxiang Fan, Jiang Zhuo et al.
NeurIPS 2025posterarXiv:2505.19641
21
citations
The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity
Parshin Shojaee, Iman Mirzadeh, Keivan Alizadeh vahid et al.
NeurIPS 2025posterarXiv:2506.06941
257
citations
Thinker: Learning to Think Fast and Slow
Stephen Chung, Wenyu Du, Jie Fu
NeurIPS 2025posterarXiv:2505.21097
5
citations
When Can Model-Free Reinforcement Learning be Enough for Thinking?
Josiah Hanna, Nicholas Corrado
NeurIPS 2025posterarXiv:2506.17124
MAGDi: Structured Distillation of Multi-Agent Interaction Graphs Improves Reasoning in Smaller Language Models
Justin Chih-Yao Chen, Swarnadeep Saha, Elias Stengel-Eskin et al.
ICML 2024poster
SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models
Xiaoxuan Wang, ziniu hu, Pan Lu et al.
ICML 2024poster