activity
20172026
most citedEmergence of Language with Multi-agent Games: Learning to Communicate with Sequences of Symbols

54 citations · 55 across the 10 of their papers we have counts for

collaborators

12 papers

cs.CL2026

The Missing Minimal Pair: Stereotype Evaluation in LLMs

Nataliya Stepanova, Ivan Titov, Emily Allaway +1

A common approach to measuring bias in Large Language Models is to compare the log-likelihoods of two contrastive stereotype sentences. We argue that such single-pair comparisons a…

cs.CL2026

Analyzing LLM Instruction Optimization for Tabular Fact Verification

Xiaotang Du, Giwon Hong, Wai-Chung Kwan +4

Instruction optimization provides a lightweight, model-agnostic approach to enhancing the reasoning performance of large language models (LLMs). This paper presents the first syste…

cs.LG2026

Operationalising the Superficial Alignment Hypothesis via Task Complexity

Tomás Vergara-Browne, Darshan Patil, Ivan Titov +3

The superficial alignment hypothesis (SAH) posits that large language models learn most of their knowledge during pre-training, and that post-training merely surfaces this knowledg…

cs.CL2025

Anthropomimetic Uncertainty: What Verbalized Uncertainty in Language Models is Missing

Dennis Ulmer, Alexandra Lorson, Ivan Titov +1

Human users increasingly communicate with large language models (LLMs), but LLMs suffer from frequent overconfidence in their output, even when its accuracy is questionable, which…

cs.LG2024

What's New in My Data? Novelty Exploration via Contrastive Generation

Masaru Isonuma, Ivan Titov

Fine-tuning is widely used to adapt language models for specific goals, often leveraging real-world data such as patient records, customer-service interactions, or web content in l…

cs.CL2024

Post-hoc Disentanglement of Textual and Acoustic Features in Pre-trained Speech Encoders

Hosein Mohebbi, Grzegorz Chrupała, Willem Zuidema +2

Pre-trained speech models build entangled internal representations, which capture a variety of features (e.g., pitch, loudness, syntax, or semantics of an utterance) in a distribut…

math.LO2024

Solovay reducibility implies S2a-reducibility

Ivan Titov

The original notion of Solovay reducibility was introduced by Robert M. Solovay (unpublished notes) in 1975 as a measure of relative randomness. The S2a-reducibility introduced by…

math.LO2024

Extending the Limit Theorem of Barmpalias and Lewis-Pye to all reals

Ivan Titov

By a celebrated result of Kučera and Slaman (DOI:10.1137/S0097539799357441), the Martin-Löf random left-c.e. reals form the highest left-c.e. Solovay degree. Barmpalias and Lewis-P…

cs.CL2024★ 1 cited

Unlearning Traces the Influential Training Data of Language Models

Masaru Isonuma, Ivan Titov

Identifying the training datasets that influence a language model's outputs is essential for minimizing the generation of harmful content and enhancing its performance. Ideally, we…

cs.CL2023

Subspace Chronicles: How Linguistic Information Emerges, Shifts and Interacts during Language Model Training

Max Müller-Eberstein, Rob van der Goot, Barbara Plank +1

Representational spaces learned via language modeling are fundamental to Natural Language Processing (NLP), however there has been limited understanding regarding how and when duri…

cs.CL2023

On the Transferability of Visually Grounded PCFGs

Yanpeng Zhao, Ivan Titov

There has been a significant surge of interest in visually grounded grammar induction in recent times. While a variety of models have been developed for the task and have demonstra…

cs.LG2017★ 54 cited

Emergence of Language with Multi-agent Games: Learning to Communicate with Sequences of Symbols

Serhii Havrylov, Ivan Titov

Learning to communicate through interaction, rather than relying on explicit supervision, is often considered a prerequisite for developing a general AI. We study a setting where t…