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Daniele Bonadiman

7 accepted papers

2025

DeAL: Decoding-time Alignment for Large Language Models

ACL 2025long

Large Language Models (LLMs) are nowadays expected to generate content aligned with human preferences. Current work focuses on alignment at model training time, through techniques such as Reinforcement Learning with Human Feedback (RLHF). However, it is unclear if such methods are an effective choic…

Cited by 0SourcePDFScholar
2024

Eliciting Better Multilingual Structured Reasoning from LLMs through Code

ACL 2024long

The development of large language models (LLM) has shown progress on reasoning, though studies have largely considered either English or simple reasoning tasks. To address this, we introduce a multilingual structured reasoning and explanation dataset, termed xSTREET, that covers four tasks across si…

Cited by 8SourcePDFScholar
2024

FLAP: Flow-Adhering Planning with Constrained Decoding in LLMs

NAACL 2024long

Planning is a crucial task for agents in task oriented dialogs (TODs). Human agents typically resolve user issues by following predefined workflows, decomposing workflow steps into actionable items, and performing actions by executing APIs in order; all of which require reasoning and planning. With…

Cited by 5SourcePDFScholar
2023

DFEE: Interactive DataFlow Execution and Evaluation Kit

AAAI 2023technical

DataFlow has been emerging as a new paradigm for building task-oriented chatbots due to its expressive semantic representations of the dialogue tasks. Despite the availability of a large dataset SMCalFlow and a simplified syntax, the development and evaluation of DataFlow-based chatbots remain chall…

2022

Injecting Domain Knowledge in Language Models for Task-oriented Dialogue Systems

EMNLP 2022main

Pre-trained language models (PLM) have advanced the state-of-the-art across NLP applications, but lack domain-specific knowledge that does not naturally occur in pre-training data. Previous studies augmented PLMs with symbolic knowledge for different downstream NLP tasks. However, knowledge bases (K…

2021

Knowledge-Driven Slot Constraints for Goal-Oriented Dialogue Systems

NAACL 2021long

In goal-oriented dialogue systems, users provide information through slot values to achieve specific goals. Practically, some combinations of slot values can be invalid according to external knowledge. For example, a combination of “cheese pizza” (a menu item) and “oreo cookies” (a topping) from an…

2020

A Study on Efficiency, Accuracy and Document Structure for Answer Sentence Selection

COLING 2020main

An essential task of most Question Answering (QA) systems is to re-rank the set of answer candidates, i.e., Answer Sentence Selection (AS2). These candidates are typically sentences either extracted from one or more documents preserving their natural order or retrieved by a search engine. Most state…