Papers by Aishvariya Priya Rathina Sabapathy
CAIR: Counterfactual-based Agent Influence Ranker for Agentic AI Workflows (2025.emnlp-main)
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Amit Giloni, Chiara Picardi, Roy Betser, Shamik Bose, Aishvariya Priya Rathina Sabapathy, Roman Vainshtein
| Challenge: | Existing methods to assess the influence of each agent on the AAW’s output perform only static structural analysis, which is unsuitable for inference time execution. |
| Approach: | They propose to use an LLM-based agent influence Ranker to assess the influence level of each agent on the AAW's output and determine which agents are the most influential. |
| Outcome: | The proposed method outperforms baseline methods and produces consistent rankings and relevancy of downstream tasks. |