1 citations · 1 across the 5 of their papers we have counts for
5 papers
SuperThoughts: Reasoning Tokens in Superposition
Zheyang Xiong, Shivam Garg, Max Yu +4
Long Chain-of-Thought (CoT) reasoning improves LLM problem-solving but is computationally expensive due to sequential token generation. While recent works explore reasoning in cont…
ECHO: Terminal Agents Learn World Models for Free
Vaishnavi Shrivastava, Piero Kauffmann, Ahmed Awadallah +1
CLI agents are the closest thing language models have to an embodied setting: the model emits commands, the terminal executes them, and the returned stream -- stdout, errors, files…
Wait, Wait, Wait... Why Do Reasoning Models Loop?
Charilaos Pipis, Shivam Garg, Vasilis Kontonis +3
Reasoning models (e.g., DeepSeek-R1) generate long chains of thought to solve harder problems, but they often loop, repeating the same text at low temperatures or with greedy decod…
Sample More to Think Less: Group Filtered Policy Optimization for Concise Reasoning
Vaishnavi Shrivastava, Ahmed Awadallah, Vidhisha Balachandran +3
Large language models trained with reinforcement learning with verifiable rewards tend to trade accuracy for length--inflating response lengths to achieve gains in accuracy. While…
Phi-4-reasoning Technical Report
Marah Abdin, Sahaj Agarwal, Ahmed Awadallah +20
We introduce Phi-4-reasoning, a 14-billion parameter reasoning model that achieves strong performance on complex reasoning tasks. Trained via supervised fine-tuning of Phi-4 on car…