5 papers
Adaptation of Agentic AI: A Survey of Post-Training, Memory, and Skills
Pengcheng Jiang, Jiacheng Lin, Zhiyi Shi +31
Large language model (LLM) agents are moving beyond prompting alone. ChatGPT marked the rise of general-purpose LLM assistants, DeepSeek showed that on-policy reinforcement learnin…
WINELL: Wikipedia Never-Ending Updating with LLM Agents
Revanth Gangi Reddy, Tanay Dixit, Jiaxin Qin +7
Wikipedia, a vast and continuously consulted knowledge base, faces significant challenges in maintaining up-to-date content due to its reliance on manual human editors. Inspired by…
The Unreasonable Effectiveness of Entropy Minimization in LLM Reasoning
Shivam Agarwal, Zimin Zhang, Lifan Yuan +2
Entropy minimization (EM) trains the model to concentrate even more probability mass on its most confident outputs. We show that this simple objective alone, without any labeled da…
mCLM: A Modular Chemical Language Model that Generates Functional and Makeable Molecules
Carl Edwards, Chi Han, Gawon Lee +11
Despite their ability to understand chemical knowledge, large language models (LLMs) remain limited in their capacity to propose novel molecules with desired functions (e.g., drug-…
Scaling Diffusion Language Models via Adaptation from Autoregressive Models
Shansan Gong, Shivam Agarwal, Yizhe Zhang +9
Diffusion Language Models (DLMs) have emerged as a promising new paradigm for text generative modeling, potentially addressing limitations of autoregressive (AR) models. However, c…