Papers with Gemini 2.5 Flash
A Benchmark and Evaluation of Automated Language of Study Extraction from Computational Linguistics Publications (2026.eacl-srw)
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| Challenge: | Language of study extraction is an aspect of computational linguistics papers that is useful for analyses of trends and diversity in computational linguists. |
| Approach: | They propose to benchmark and evaluate automated language of study extraction from computational linguistics papers. |
| Outcome: | The proposed language extraction benchmarks show that they can extract languages from papers with accuracy without high computational costs. |
AI for Climate Finance: Agentic Retrieval and Multi-Step Reasoning for Early Warning System Investments (2026.eacl-demo)
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Ario Saeid Vaghefi, Aymane Hachcham, Veronica Grasso, Nakiete Msemo, Chiara Colesanti Senni, Markus Leippold
| Challenge: | EWS financial flows are opaque and lack standardized labels, structures, and terminology for EWS-related spending. |
| Approach: | They propose an agent-based Retrieval-Augmented Generation system that uses hybrid retrieval and internal chain-of-thought reasoning to extract relevant financial data and classify EWS investments. |
| Outcome: | The proposed system outperforms four alternatives on multi-label classification and budget allocation on an annotated CREWS Fund corpus. |
GAMBIT: A Gamified Jailbreak Framework for Multimodal Large Language Models (2026.acl-long)
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| Challenge: | Existing attacks focus on increasing the complexity of the modified visual task and do not explicitly leverage the model’s own reasoning incentives. |
| Approach: | They propose a framework that decomposes and reassembles harmful visual semantics and constructs a gamified scene that drives the model to explore, reconstruct intent and answer as part of winning the game. |
| Outcome: | Experiments on reasoning and non-reasoning MLLMs show that the proposed framework outperforms baseline models on both vision and text. |