1 citations · 1 across the 6 of their papers we have counts for
18 papers
The Bitter Lesson of Tool Calling
Ishan Patel, Sahil Sen, Elias Lumer +1
Tool use transforms LLMs into agents that act beyond their training data, and for code-capable models, programmatic tool calling extends this further by replacing rigid JSON calls…
Do You Need a Frontier Model as a Citation Verifier? Benchmarking Rubric LLMs for Deep-Research Source Attribution
Ethan Leung, Elias Lumer, Corey Feld +3
Reinforcement learning increasingly relies on an LLM judge to score each rubric criterion, and that judge acts as the reward model during training. Before such a signal can be trus…
Recursive Agent Harnesses
Elias Lumer, Sahil Sen, Kevin Paul +1
Recursive language models (RLMs) showed that recursion over model calls is an effective strategy for long-context reasoning, and production coding agents have begun to write code t…
Is Grep All You Need? How Agent Harnesses Reshape Agentic Search
Sahil Sen, Akhil Kasturi, Elias Lumer +2
Recent advances in Large Language Model (LLM) agents have enabled complex agentic workflows where models autonomously retrieve information, call tools, and reason over large corpor…
Ask Early, Ask Late, Ask Right: When Does Clarification Timing Matter for Long-Horizon Agents?
Anmol Gulati, Hariom Gupta, Elias Lumer +2
Long-horizon AI agents execute complex workflows spanning hundreds of sequential actions, yet a single wrong assumption early on can cascade into irreversible errors. When instruct…
Cited but Not Verified: Parsing and Evaluating Source Attribution in LLM Deep Research Agents
Hailey Onweller, Elias Lumer, Austin Huber +3
Large language models (LLMs) power deep research agents that synthesize information from hundreds of web sources into cited reports, yet these citations cannot be reliably verified…