2 citations · 3 across the 6 of their papers we have counts for
9 papers
GAW-PO: Preference Optimization with Gradient-Aligned Token Weights
Andreea Dutulescu, Stefan Ruseti, Mihai Masala +2
Most preference optimization methods, such as Direct Preference Optimization (DPO), apply preference supervision at the response level, although autoregressive language models are…
Neural Grammatical Error Correction for Romanian
Teodor-Mihai Cotet, Stefan Ruseti, Mihai Dascalu
Resources for Grammatical Error Correction (GEC) in non-English languages are scarce, while available spellcheckers in these languages are mostly limited to simple corrections and…
Value-Aware Numerical Representations for Transformer Language Models
Andreea Dutulescu, Stefan Ruseti, Mihai Dascalu
Transformer-based language models often achieve strong results on mathematical reasoning benchmarks while remaining fragile on basic numerical understanding and arithmetic operatio…
Training Language Models with homotokens Leads to Delayed Overfitting
Adrian Cosma, Stefan Ruseti, Emilian Radoi +1
Subword tokenization introduces a computational layer in language models where many distinct token sequences decode to the same surface form and preserve meaning, yet induce differ…
The Strawberry Problem: Emergence of Character-level Understanding in Tokenized Language Models
Adrian Cosma, Stefan Ruseti, Emilian Radoi +1
Despite their remarkable progress across diverse domains, Large Language Models (LLMs) consistently fail at simple character-level tasks, such as counting letters in words, due to…
How Hard is this Test Set? NLI Characterization by Exploiting Training Dynamics
Adrian Cosma, Stefan Ruseti, Mihai Dascalu +1
Natural Language Inference (NLI) evaluation is crucial for assessing language understanding models; however, popular datasets suffer from systematic spurious correlations that arti…
Romanian Diacritics Restoration Using Recurrent Neural Networks
Stefan Ruseti, Teodor-Mihai Cotet, Mihai Dascalu
Diacritics restoration is a mandatory step for adequately processing Romanian texts, and not a trivial one, as you generally need context in order to properly restore a character.…
Answering questions by learning to rank -- Learning to rank by answering questions
George-Sebastian Pîrtoacă, Traian Rebedea, Stefan Ruseti
Answering multiple-choice questions in a setting in which no supporting documents are explicitly provided continues to stand as a core problem in natural language processing. The c…
Improving Retrieval-Based Question Answering with Deep Inference Models
George-Sebastian Pirtoaca, Traian Rebedea, Stefan Ruseti
Question answering is one of the most important and difficult applications at the border of information retrieval and natural language processing, especially when we talk about com…