Francesca Toni
Professor in Computational Logic
Works on computational argumentation for explainable AI, knowledge representation, non-monotonic reasoning and argument mining.
Francesca Toni's lab at Imperial works on trustworthy & safe ML, reasoning & neuro-symbolic AI and reasoning & agents. 30 papers since 2023, 9 at top venues, mostly AAMAS and AAAI. 7 PhD students. 19 alumni. Applications close .
At a glance
- papers, 2023–2026
- 8/ year
- at T1 venues
- 30%
- PhD students
- 7
- MS students
- 0
- alumni listed
- 19
Papers by yearfrom the lab homepage, 2023–2026
- 6 papers2026 · T1 5 · collecting
- 24 papers2025 · T1 4
- 0 papers2024 · T1 0
- 0 papers2023 · T1 0
T1 venuesOtherVenues: AAMAS, AAAI, KR, EMNLP, ICLR
Research focuspaper titles that use each topic's words
- argumentation9 papers
- Reasoning & neuro-symbolic AI4 papers
- Reasoning & agents3 papers
- Trustworthy & safe ML1 paper
- knowledge representation0 papers
Paper list
From the lab homepage.
20266 papers
- AAMAS (T1)ArgLLM-App: an interactive system for argumentative reasoning with large language models (opens in a new tab)
- AAAI (T1)Argumentative debates for transparent bias detection (opens in a new tab)
- Knowledge representation and ReasoningContestability in edge-weighted quantitative bipolar argumentation frameworks
- AAAI (T1)Heterogeneous graph neural networks for assumption-based argumentation (opens in a new tab)
- AAMAS (T1)Strength change explanations in quantitative argumentation
- ICLR (T1)Synthesising counterfactual explanations via label-conditional Gaussian mixture variational autoencoders
202524 papers
- KRA methodology for incompleteness-tolerant and modular gradual semantics for argumentative statement graphs (opens in a new tab)
- Proceedings of the European Conference on Artificial Intelligence (ECAI ) - Demo TrackADA-X: an online system for fully automated, explainable review aggregation (opens in a new tab)
- Autonomous Agents and Multi-Agent SystemsAggregating bipolar opinions through bipolar assumption-based argumentation (opens in a new tab)
- Pages: 5216-5223Argumentation for ExplainableWorkforce Optimisation (opens in a new tab)
- Pages: 121-132Argumentative LLMs for Legal Information Entailment (opens in a new tab)
- European Conference on Artificial IntelligenceArgumentatively coherent judgmental forecasting (opens in a new tab)
- International Joint Conference on Artificial Intelligence (IJCAI)Counterfactual explanations under model multiplicity and their use in computational argumentation (opens in a new tab)
- EMNLP (T1)Evaluating uncertainty quantification methods in argumentative large language models
- AI MagazineExplainable AI, energy and critical infrastructure systems (opens in a new tab)
- PAISExplainable prediction of the mechanical properties of composites with CNNs (opens in a new tab)
- The ACM/SIGAPP Symposium On Applied ComputingExplainable reinforcement learning for Formula One race strategy
- PAISExploring the effect of explanation content and format on user comprehension and trust in healthcare (opens in a new tab)
Where alumni went19 listed
Apply to Imperial2027 (Apr/Oct)
Computing PhD
- Round
- Round 2 (1 Dec 2026)
- Opens
- —
- GRE
- See program page
- English
- See program page
- Fee
- none
Confirmed on the program page.
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- USStanford
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- USGeorgia Tech
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- The lab homepage
- Members
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