Papers by Rafael Ferreira
Plan-Grounded Large Language Models for Dual Goal Conversational Settings (2024.eacl-long)
Copied to clipboard
| Challenge: | Existing studies show that LLMs can follow user instructions, but it is unclear how they can lead a plan-grounded conversation in mixed-initiative settings where instructions flow in both directions of the conversation. |
| Approach: | They propose a dual-purpose mixed-initiative conversational setting where the LLM grounds the conversation on an arbitrary plan and seeks to satisfy both a procedural plan and user instructions. |
| Outcome: | The proposed model achieves 2.1x improvement over a strong baseline and good generalization to unseen domains. |
Multi-trait User Simulation with Adaptive Decoding for Conversational Task Assistants (2024.findings-emnlp)
Copied to clipboard
| Challenge: | Existing methods to model conversational traits are costly and time consuming. |
| Approach: | They propose a method that generates diverse user profiles at decoding-time by sampling from trait-specific Language Models. |
| Outcome: | The proposed method generates diverse user profiles at decoding-time without fine-tuning. |
DeepResearch Retail: Benchmarking Tool-Augmented Deep Research in the E-Commerce Domain (2026.acl-industry)
Copied to clipboard
| Challenge: | Existing DR systems are largely web-centric and do not incorporate structured, domain-specific, and personalized information accessible through internal API tools. |
| Approach: | They propose a framework grounded in real-world e-commerce data for assessing Deep Research with tools in realistic commercial settings. |
| Outcome: | The proposed framework evaluates factual faithfulness and multidimensional response quality when reasoning over heterogeneous web and internal data sources. |