Ronny Luss

19 papers · 2007–2025 · 8 conferences · across top CS/AI conferences

Achievements

+12 more ↓

🌉 Interdisciplinary Bridge 🌍 Conference Polyglot (8) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🏃 Academic Marathon (18)

🌈 Renaissance Researcher (7) 🐝 Cross-Pollinator (14) 🌍 Conference Polyglot (8) 🌟 Keyword Trendsetter Combo (5) 👥 Mega-Team (20) 🏆 Grand Slam 🏆 Keyword Champion 🧬 Topic Evolution 🤝 Dynamic Duo (10) 💎 Century Club (19) 🗃️ Keyword Collector (76) 📈 Trend Setter

Conferences

NIPS (4) EMNLP (3) ICLR (3) AAAI (2) ACL (2) ICML (2) IJCAI (2) JMLR (1)

Top co-authors

Amit Dhurandhar (10) Karthikeyan Shanmugam (6) Pin-Yu Chen (4) Prasanna Sattigeri (4) Debarun Bhattacharjya (3) Achille Fokoue (3) Kush R. Varshney (3) Dennis Wei (3) Karthikeyan Natesan Ramamurthy (2) Vijay Arya (2)

Keywords

explainable ai (3) model interpretability (3) convex optimization (2) neural network (2) feature attribution (2) sparse training (2) large language model (2) contrastive explanation (2) transfer learning (2) neural network training (1) text classification (1) natural language processing (1) knowledge transfer (1) knowledge distillation (1) semi-supervised learning (1) neural network pruning (1) isotonic regression (1) classification (1) reinforcement learning (1) model adaptation (1)

Papers

Multi-Level Explanations for Generative Language Models ACL 2025 Shedding Light on Time Series Classification using Interpretability Gated Networks ICLR 2025 Sparsity May Be All You Need: Sparse Random Parameter Adaptation EMNLP 2025 ComVas: Contextual Moral Values Alignment System IJCAI 2024 NeuroPrune: A Neuro-inspired Topological Sparse Training Algorithm for Large Language Models ACL 2024 Weighted Clock Logic Point Process ICLR 2023 Probabilistic Rule Induction from Event Sequences with Logical Summary Markov Models IJCAI 2023 Local Explanations for Reinforcement Learning AAAI 2023 Self-Supervised Rule Learning to Link Text Segments to Relational Elements of Structured Knowledge EMNLP 2023 Auto-Transfer: Learning to Route Transferable Representations ICLR 2022 AI Explainability 360: Impact and Design AAAI 2022 Let the CAT out of the bag: Contrastive Attributed explanations for Text EMNLP 2022 AI Explainability 360: An Extensible Toolkit for Understanding Data and Machine Learning Models JMLR 2020 Enhancing Simple Models by Exploiting What They Already Know ICML 2020 Beyond Backprop: Online Alternating Minimization with Auxiliary Variables ICML 2019 Improving Simple Models with Confidence Profiles NIPS 2018 Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives NIPS 2018 Decomposing Isotonic Regression for Efficiently Solving Large Problems NIPS 2010 Support Vector Machine Classification with Indefinite Kernels NIPS 2007