Papers by Timothée Bernard
The Emergence of High-Level Semantics in a Signaling Game (2024.starsem-1)
Copied to clipboard
| Challenge: | a symbol grounding problem has been raised in recent years in AI . we show that neural agents can communicate high-level semantic concepts . |
| Approach: | They propose to use an adversarial agent to train neural agents in a signaling game . they show that the agents can communicate high-level semantic concepts rather than low-level features . |
| Outcome: | The proposed method can learn to communicate high-level semantic concepts . it also produces an appropriate training signal when no other method is available . |
So many design choices: Improving and interpreting neural agent communication in signaling games (2023.findings-acl)
Copied to clipboard
| Challenge: | Emergent language games are experimental protocols designed to model how communication may arise among a group of agents. |
| Approach: | They propose to adopt a signaling game in which a sender is exposed to an image and generates a sequence of symbols that is transmitted to a receiver. |
| Outcome: | The proposed language improves when the sender is exposed to an image and generates a sequence of symbols that is transmitted to a receiver. |
On the Relation Between Fine-Tuning, Topological Properties, and Task Performance in Sense-Enhanced Embeddings (2025.acl-long)
Copied to clipboard
| Challenge: | Enhanced word embeddings do not align well with word senses, resulting in poor performance on word sense identification tasks. |
| Approach: | They propose to use two methods to fine-tune embeddings to identify the topological properties that contribute to sense-enhanced embeddables. |
| Outcome: | The proposed methods improve the embeddings’ ability to capture nuanced semantic distinctions while reducing their expressiveness. |
NuNER: Entity Recognition Encoder Pre-training via LLM-Annotated Data (2024.emnlp-main)
Copied to clipboard
| Challenge: | Named Entity Recognition (NER) is a core component of natural language processing, present in a variety of applications such as medical coding, financial news analysis, or legal documents parsing. |
| Approach: | They propose to use Large Language Models (LLMs) to create NuNER, a compact language representation model specialized in the Named Entity Recognition task. |
| Outcome: | The proposed model outperforms similar-sized foundation models in the few-shot regime and is based on a human-annotated dataset. |
Improving Word Sense Induction through Adversarial Forgetting of Morphosyntactic Information (2024.starsem-1)
Copied to clipboard
| Challenge: | Contextualized word representations from pre-trained language models encode more information than is necessary for the identification of word senses and some of this information affect performance negatively in unsupervised settings. |
| Approach: | They propose to use a framework to erase specific information from pre-trained word models and create feature-invariant representations that are invariant to these ‘nuisance features’. |
| Outcome: | The proposed framework erases information from the representations of pre-trained language models, thereby creating feature-invariant representations. |
Mandarinograd: A Chinese Collection of Winograd Schemas (2020.lrec-1)
Copied to clipboard
| Challenge: | Mandarinograd is a corpus of Winograd Schemas in Mandarin Chinese . WS are hard to collect and few datasets are publicly available . |
| Approach: | They introduce a corpus of Winograd Schemas in Mandarin Chinese . they describe the difficulties faced when building the corpus and explain how they overcome the anomalies. |
| Outcome: | The proposed corpus of Winograd Schemas in Mandarin Chinese is hard to build and resistant to statistical methods. |
Tabouid: a Wikipedia-based word guessing game (2020.acl-demos)
Copied to clipboard
| Challenge: | Using Wikipedia articles, we generate word-guessing games using a set of NLP and machine-learning techniques. |
| Approach: | They propose a system which uses Wikipedia to generate word-guessing games. |
| Outcome: | The proposed game is based on Tabouid, a word-guessing board game originally published by Parker Brothers in 1989. |
What Meaning-Form Correlation Has to Compose With: A Study of MFC on Artificial and Natural Language (2020.coling-main)
Copied to clipboard
| Challenge: | Compositionality is a widely discussed property of natural languages, although its exact definition has been elusive. |
| Approach: | They propose that compositionality can be measured by measuring meaning-form correlation . they analyze three sets of languages: artificial toy languages tailored to be compositional . |
| Outcome: | The proposed method can assess compositionality on three sets of languages . linguistic phenomena such as synonymy and ungrounded stop-words weigh on the results . |
Multiple Tasks Integration: Tagging, Syntactic and Semantic Parsing as a Single Task (2021.eacl-main)
Copied to clipboard
| Challenge: | Existing systems that bypass intermediate levels of analysis are prone to error propagation and are therefore free from interference. |
| Approach: | They propose a multitask paradigm orthogonal to weight sharing that uses multiple tasks to process input iteratively but concurrently at multiple levels of analysis. |
| Outcome: | The proposed model uses reinforcement learning and release from sequential constraints to improve the quality of the syntactic and semantic parses. |