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Traian Rebedea

11 accepted papers

2025

AEGIS2.0: A Diverse AI Safety Dataset and Risks Taxonomy for Alignment of LLM Guardrails

NAACL 2025long

As Large Language Models (LLMs) and generative AI become increasingly widespread, concerns about content safety have grown in parallel. Currently, there is a clear lack of high-quality, human-annotated datasets that address the full spectrum of LLM-related safety risks and are usable for commercial…

2025

MultiMatch: Multihead Consistency Regularization Matching for Semi-Supervised Text Classification

EMNLP 2025

We introduce **MultiMatch**, a novel semi-supervised learning (SSL) algorithm combining the paradigms of co-training and consistency regularization with pseudo-labeling. At its core, MultiMatch features a three-fold pseudo-label weighting module designed for selecting and filtering pseudo-labels bas

2025

Safety Through Reasoning: An Empirical Study of Reasoning Guardrail Models

EMNLP 2025

Reasoning-based language models have demonstrated strong performance across various domains, with the most notable gains seen in mathematical and coding tasks. Recent research has shown that reasoning also offers significant benefits for LLM safety and guardrail applications. In this work, we conduc

Cited by 0SourcePDFScholar
2024

CantTalkAboutThis: Aligning Language Models to Stay on Topic in Dialogues

EMNLP 2024finding

Recent advancements in instruction-tuning datasets have predominantly focused on specific tasks like mathematical or logical reasoning. There has been a notable gap in data designed for aligning language models to maintain topic relevance in conversations - a critical aspect for deploying chatbots t…

2024

GunStance: Stance Detection for Gun Control and Gun Regulation

ACL 2024long

The debate surrounding gun control and gun regulation in the United States has intensified in the wake of numerous mass shooting events. As perspectives on this matter vary, it becomes increasingly important to comprehend individuals’ positions. Stance detection, the task of determining an author’s…

2024

Unsupervised Extraction of Dialogue Policies from Conversations

EMNLP 2024main

Dialogue policies play a crucial role in developing task-oriented dialogue systems, yet their development and maintenance are challenging and typically require substantial effort from experts in dialogue modeling. While in many situations, large amounts of conversational data are available for the t…

Cited by 1SourcePDFScholar
2024

“Vorbești Românește?” A Recipe to Train Powerful Romanian LLMs with English Instructions

EMNLP 2024finding

In recent years, Large Language Models (LLMs) have achieved almost human-like performance on various tasks. While some LLMs have been trained on multilingual data, most of the training data is in English; hence, their performance in English greatly exceeds other languages. To our knowledge, we are t…

2022

Multimodal Semi-supervised Learning for Disaster Tweet Classification

COLING 2022main

During natural disasters, people often use social media platforms, such as Twitter, to post information about casualties and damage produced by disasters. This information can help relief authorities gain situational awareness in nearly real time, and enable them to quickly distribute resources wher…

2021

LiRo: Benchmark and leaderboard for Romanian language tasks

NeurIPS 2021poster

Recent advances in NLP have been sustained by the availability of large amounts of data and standardized benchmarks, which are not available for many languages. As a small step towards addressing this we propose LiRo, a platform for benchmarking models on the Romanian language on nine standard tasks…

Cited by 32SourcecodeScholar
2020

Neural Approaches for Natural Language Interfaces to Databases: A Survey

COLING 2020main

A natural language interface to databases (NLIDB) enables users without technical expertise to easily access information from relational databases. Interest in NLIDBs has resurged in the past years due to the availability of large datasets and improvements to neural sequence-to-sequence models. In t…

Cited by 26SourcePDFScholar