Papers by Apurva Gandhi
AgentDiagnose: An Open Toolkit for Diagnosing LLM Agent Trajectories (2025.emnlp-demos)
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| Challenge: | Large Language Model (LLM) agents produce rich, multi-step trajectories that interleave observations, internal reasoning, and tool actions. |
| Approach: | They propose an open-source framework for diagnosing agent trajectories that quantifies five core agentic competencies and a visualization module that highlights trajectory semantics. |
| Outcome: | The proposed framework is extensible and compatible with most agent trajectories. |
SLATE: A Sequence Labeling Approach for Task Extraction from Free-form Inked Content (2022.emnlp-industry)
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Apurva Gandhi, Ryan Serrao, Biyi Fang, Gilbert Antonius, Jenna Hong, Tra My Nguyen, Sheng Yi, Ehi Nosakhare, Irene Shaffer, Soundararajan Srinivasan
| Challenge: | SLATE is a sequence labeling approach for extracting tasks from free-form content . past approaches for task extraction from typed content focus on building separate sentence-level task classification models. |
| Approach: | They propose a sequence labeling approach for extracting tasks from free-form content . they use a single, low-latency sequence labelling approach to perform sentence segmentation and classification . |
| Outcome: | The proposed model outperforms a baseline model and achieves 84.4% task F1 score and 88.4% boundary similarity score. |