Prasanna Sattigeri

43 papers · 2017–2026 · 14 conferences · across top CS/AI conferences

Achievements

+14 more ↓

🌍 Conference Polyglot (14) 🧭 Keyword Pioneer 🗺️ Taxonomy Completionist (12) 🌉 Interdisciplinary Bridge 🏃 Academic Marathon (8)

🏃 Academic Marathon (8) 🐝 Cross-Pollinator (11) 🌈 Renaissance Researcher (8) 👥 Mega-Team (22) 🧬 Topic Evolution 👑 Triple Crown 🏆 Grand Slam 🚀 Conference Pioneer 🗃️ Keyword Collector (162) ❓ The Questioner (2) 💎 Century Club (41) 📈 Trend Setter 🔥 Unstoppable (9) ⚡ Prolific Year (7)

Conferences

NIPS (12) AAAI (6) ACL (3) ECCV (3) ICML (3) JMLR (3) AISTATS (2) EMNLP (2) ICLR (2) NAACL (2) UAI (2) EACL (1) ICCV (1) IJCAI (1)

Top co-authors

Dennis Wei (9) Kush R. Varshney (8) Subhro Das (8) Leonid Karlinsky (7) Rogerio Feris (7) Karthikeyan Natesan Ramamurthy (6) Manish Nagireddy (6) Ali Tajer (6) Soumya Ghosh (6) Karthikeyan Shanmugam (6)

Keywords

large language model (9) uncertainty quantification (5) transfer learning (3) causal bandit (2) pretrained model (2) intervention target (2) value alignment (2) precision matrix (2) out-of-distribution detection (2) generative adversarial network (2) image classification (2) causal discovery (2) explainable ai (2) human-ai interaction (2) model interpretability (2) structural equation model (2) causal inference (2) mutual information (2) weakly supervised learning (2) hallucination detection (2)

Papers

Answering the Wrong Question: Reasoning Trace Inversion for Abstention in LLMs ACL 2026 Multi-component Causal Tracing in Large Language Models ACL 2026 Evaluating the Prompt Steerability of Large Language Models NAACL 2025 Multi-Level Explanations for Generative Language Models ACL 2025 Granite Guardian: Comprehensive LLM Safeguarding NAACL 2025 Are Uncertainty Quantification Capabilities of Evidential Deep Learning a Mirage? NIPS 2024 WikiContradict: A Benchmark for Evaluating LLMs on Real-World Knowledge Conflicts from Wikipedia NIPS 2024 ComVas: Contextual Moral Values Alignment System IJCAI 2024 Thermometer: Towards Universal Calibration for Large Language Models ICML 2024 Value Alignment from Unstructured Text EMNLP 2024 Language Models in Dialogue: Conversational Maxims for Human-AI Interactions EMNLP 2024 Fourier Neural Operators for Arbitrary Resolution Climate Data Downscaling JMLR 2024 Causal Bandits with General Causal Models and Interventions AISTATS 2024 Graph-based Uncertainty Metrics for Long-form Language Model Generations NIPS 2024 Interventional Causal Discovery in a Mixture of DAGs NIPS 2024 Reliable Gradient-free and Likelihood-free Prompt Tuning EACL 2023 Efficient Equivariant Transfer Learning from Pretrained Models NIPS 2023 Effective Human-AI Teams via Learned Natural Language Rules and Onboarding NIPS 2023 Equi-Tuning: Group Equivariant Fine-Tuning of Pretrained Models AAAI 2023 Post-hoc Uncertainty Learning Using a Dirichlet Meta-Model AAAI 2023 Who Should Predict? Exact Algorithms For Learning to Defer to Humans AISTATS 2023 Causal Bandits for Linear Structural Equation Models JMLR 2023 AI Explainability 360: Impact and Design AAAI 2022 Fair Infinitesimal Jackknife: Mitigating the Influence of Biased Training Data Points Without Refitting NIPS 2022 Intervention target estimation in the presence of latent variables UAI 2022 Selective Regression under Fairness Criteria ICML 2022 AdaFuse: Adaptive Temporal Fusion Network for Efficient Action Recognition ICLR 2021 Scalable Intervention Target Estimation in Linear Models NIPS 2021 Fair Selective Classification Via Sufficiency ICML 2021 StarNet: towards Weakly Supervised Few-Shot Object Detection AAAI 2021 Detector-Free Weakly Supervised Grounding by Separation ICCV 2021 Conditionally independent data generation UAI 2021 AR-Net: Adaptive Frame Resolution for Efficient Action Recognition ECCV 2020 OnlineAugment: Online Data Augmentation with Less Domain Knowledge ECCV 2020 TAFSSL: Task-Adaptive Feature Sub-Space Learning for few-shot classification ECCV 2020 A Natural Language Processing System for Extracting Evidence of Drug Repurposing from Scientific Publications AAAI 2020 Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors AAAI 2020 AI Explainability 360: An Extensible Toolkit for Understanding Data and Machine Learning Models JMLR 2020 Optimizing Mode Connectivity via Neuron Alignment NIPS 2020 Learning New Tricks From Old Dogs: Multi-Source Transfer Learning From Pre-Trained Networks NIPS 2019 Co-regularized Alignment for Unsupervised Domain Adaptation NIPS 2018 Variational Inference of Disentangled Latent Concepts from Unlabeled Observations ICLR 2018 Semi-supervised Learning with GANs: Manifold Invariance with Improved Inference NIPS 2017