8 papers
Reflective Prompt Optimization of a Deep-Research Agent: A Topic-Disjoint, Multi-Seed Protocol for Measuring Transferable Gains and Prompt-Level Overfitting
Elias Lumer, Sahil Sen, Vamse Kumar Subbiah +1
Prompt optimization is an attractive alternative to reinforcement learning for adapting language-model agents, since it is cheap and produces human-readable artifacts. On factual t…
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…
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…
Chronos: Temporal-Aware Conversational Agents with Structured Event Retrieval for Long-Term Memory
Sahil Sen, Elias Lumer, Anmol Gulati +1
Recent advances in Large Language Models (LLMs) have enabled conversational AI agents to engage in extended multi-turn interactions spanning weeks or months. However, existing memo…
Beyond Rows to Reasoning: Agentic Retrieval for Multimodal Spreadsheet Understanding and Editing
Anmol Gulati, Sahil Sen, Waqar Sarguroh +1
Recent advances in multimodal Retrieval-Augmented Generation (RAG) enable Large Language Models (LLMs) to analyze enterprise spreadsheet workbooks containing millions of cells, cro…
From Rows to Reasoning: A Retrieval-Augmented Multimodal Framework for Spreadsheet Understanding
Anmol Gulati, Sahil Sen, Waqar Sarguroh +1
Large Language Models (LLMs) struggle to reason over large-scale enterprise spreadsheets containing thousands of numeric rows, multiple linked sheets, and embedded visual content s…