Papers by Adrián Bazaga
Learning to Reason Over Time: Timeline Self-Reflection for Improved Temporal Reasoning in Language Models (2025.acl-long)
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| Challenge: | Large Language Models struggle with temporal reasoning, which requires processing time-related information such as event sequencing, durations, and inter-temporal relationships. |
| Approach: | They propose a framework that enhances the temporal reasoning abilities of Large Language Models (LLMs) by combining timeline construction with iterative self-reflection. |
| Outcome: | The proposed framework improves the temporal reasoning abilities of large language models and improves traceability of the inference process. |
HyperBERT: Mixing Hypergraph-Aware Layers with Language Models for Node Classification on Text-Attributed Hypergraphs (2024.findings-emnlp)
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| Challenge: | Existing methods to learn informative data representations on text-attributed hypergraphs struggle to capture full extent of hypergraph structural information and rich linguistic attributes inherent in the nodes attributes. |
| Approach: | They propose to augment a pre-trained BERT model with specialized hypergraph-aware layers for the task of node classification. |
| Outcome: | The proposed model outperforms existing methods on five challenging text-attributed hypergraph node classification benchmarks. |