7 papers
AdaEvolve: Adaptive LLM Driven Zeroth-Order Optimization
Mert Cemri, Shubham Agrawal, Akshat Gupta +9
The paradigm of automated program generation is shifting from one-shot generation to inference-time search, where Large Language Models (LLMs) function as semantic mutation operato…
Agentic Test-Time Scaling for WebAgents
Nicholas Lee, Lutfi Eren Erdogan, Chris Joseph John +4
Test-time scaling has become a standard way to improve performance and boost reliability of neural network models. However, its behavior on agentic, multi-step tasks remains less w…
Plan-and-Act: Improving Planning of Agents for Long-Horizon Tasks
Lutfi Eren Erdogan, Nicholas Lee, Sehoon Kim +5
Large language models (LLMs) have shown remarkable advancements in enabling language agents to tackle simple tasks. However, applying them for complex, multi-step, long-horizon tas…
Stochastic Communication Avoidance for Recommendation Systems
Lutfi Eren Erdogan, Vijay Anand Raghava Kanakagiri, Kurt Keutzer +1
One of the major bottlenecks for efficient deployment of neural network based recommendation systems is the memory footprint of their embedding tables. Although many neural network…
TinyAgent: Function Calling at the Edge
Lutfi Eren Erdogan, Nicholas Lee, Siddharth Jha +7
Recent large language models (LLMs) have enabled the development of advanced agentic systems that can integrate various tools and APIs to fulfill user queries through function call…
Efficient and Scalable Estimation of Tool Representations in Vector Space
Suhong Moon, Siddharth Jha, Lutfi Eren Erdogan +4
Recent advancements in function calling and tool use have significantly enhanced the capabilities of large language models (LLMs) by enabling them to interact with external informa…