4 papers · 1 filter
Foundations of Top- Decoding For Language Models
Georgy Noarov, Soham Mallick, Tao Wang +5
Top- decoding is a widely used method for sampling from LLMs: at each token, only the largest next-token-probabilities are kept, and the next token is sampled after re-norma…
Statistical Early Stopping for Reasoning Models
Yangxinyu Xie, Tao Wang, Soham Mallick +6
While LLMs have seen substantial improvement in reasoning capabilities, they also sometimes overthink, generating unnecessary reasoning steps, particularly under uncertainty, given…
WildfireGPT: Tailored Large Language Model for Wildfire Analysis
Yangxinyu Xie, Bowen Jiang, Tanwi Mallick +10
Recent advancement of large language models (LLMs) represents a transformational capability at the frontier of artificial intelligence. However, LLMs are generalized models, traine…
Towards Rationality in Language and Multimodal Agents: A Survey
Bowen Jiang, Yangxinyu Xie, Xiaomeng Wang +6
This work discusses how to build more rational language and multimodal agents and what criteria define rationality in intelligent systems. Rationality is the quality of being guide…