Irina Rish
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
63
Venues
21
Active years
1994–2026
Best venue rank
A*
Where they publish
Papers
63 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | AAAI | Persistent Instability in LLM's Personality Measurements: Effects of Scale, Reasoning, and Conversation History. | Tommaso Tosato, Saskia Helbling, Yorguin Jos Mantilla Ramos, Mahmood Hegazy, Alberto Tosato, David John Lemay, Irina Rish, Guillaume Dumas |
| 2026 | ACL | GitChameleon 2.0: Evaluating AI Code Generation Against Python Library Version Incompatibilities. | Diganta Misra, Nizar Islah, Victor May, Brice Rauby, Zihan Wang, Justine Gehring, Antonio Orvieto, Muawiz Sajjad Chaudhary, Eilif B. Muller, Irina Rish, Samira Ebrahimi Kahou, Massimo Caccia |
| 2025 | ACL | Training Dynamics Underlying Language Model Scaling Laws: Loss Deceleration and Zero-Sum Learning. | Andrei Mircea, Supriyo Chakraborty, Nima Chitsazan, Irina Rish, Ekaterina Lobacheva |
| 2025 | ACL | Scaling Laws and Efficient Inference for Ternary Language Models. | Tejas Vaidhya, Ayush Kaushal, Vineet Jain, Francis Couture Harpin, Prashant Shishodia, Majid Behbahani, Yuriy Nevmyvaka, Irina Rish |
| 2025 | EMNLP | CAVE : Detecting and Explaining Commonsense Anomalies in Visual Environments. | Rishika Bhagwatkar, Syrielle Montariol, Angelika Romanou, Beatriz Borges, Irina Rish, Antoine Bosselut |
| 2025 | ICLR | Handling Delay in Real-Time Reinforcement Learning. | Ivan Anokhin, Rishav Rishav, Matthew Riemer, Stephen Chung, Irina Rish, Samira Ebrahimi Kahou |
| 2025 | ICLR | Seq-VCR: Preventing Collapse in Intermediate Transformer Representations for Enhanced Reasoning. | Md Rifat Arefin, Gopeshh Subbaraj, Nicolas Gontier, Yann LeCun, Irina Rish, Ravid Shwartz-Ziv, Christopher Pal |
| 2025 | ICLR | Non-Adversarial Inverse Reinforcement Learning via Successor Feature Matching. | Arnav Kumar Jain, Harley Wiltzer, Jesse Farebrother, Irina Rish, Glen Berseth, Sanjiban Choudhury |
| 2025 | ICLR | Surprising Effectiveness of pretraining Ternary Language Model at Scale. | Ayush Kaushal, Tejas Vaidhya, Arnab Kumar Mondal, Tejas Pandey, Aaryan Bhagat, Irina Rish |
| 2025 | ICLR | Enabling Realtime Reinforcement Learning at Scale with Staggered Asynchronous Inference. | Matthew Riemer, Gopeshh Subbaraj, Glen Berseth, Irina Rish |
| 2025 | ICML | Context is Key: A Benchmark for Forecasting with Essential Textual Information. | Andrew Robert Williams, Arjun Ashok, tienne Marcotte, Valentina Zantedeschi, Jithendaraa Subramanian, Roland Riachi, James Requeima, Alexandre Lacoste, Irina Rish, Nicolas Chapados, Alexandre Drouin |
| 2025 | ICML | AI for Global Climate Cooperation: Modeling Global Climate Negotiations, Agreements, and Long-Term Cooperation in RICE-N. | Tianyu Zhang, Andrew Robert Williams, Phillip Wozny, Kai-Hendrik Cohrs, Koen Ponse, Marco Jiralerspong, Soham R. Phade, Sunil Srinivasa, Lu Li, Yang Zhang, Prateek Gupta, Erman Acar, Irina Rish, Yoshua Bengio, Stephan Zheng |
| 2024 | AAAI | Dance of the Neurons: Unraveling Sex from Brain Signals (short paper). | Mohammad-Javad Darvishi Bayazi, Mohammad Sajjad Ghaemi, Jocelyn Faubert, Irina Rish |
| 2024 | CogSci | Decision-Making Paradoxes in Humans vs Machines: The case of the Allais and Ellsberg Paradoxes. | Ardavan Salehi Nobandegani, Irina Rish, Thomas R. Shultz |
| 2024 | EMNLP | Improving Adversarial Robustness in Vision-Language Models with Architecture and Prompt Design. | Rishika Bhagwatkar, Shravan Nayak, Pouya Bashivan, Irina Rish |
| 2024 | ICML | Unsupervised Concept Discovery Mitigates Spurious Correlations. | Md Rifat Arefin, Yan Zhang, Aristide Baratin, Francesco Locatello, Irina Rish, Dianbo Liu, Kenji Kawaguchi |
| 2024 | IJCAI | Knowledge Distillation in Federated Learning: A Practical Guide. | Alessio Mora, Irene Tenison, Paolo Bellavista, Irina Rish |
| 2023 | CogSci | AI Agents Learn to Trust. | Ardavan Salehi Nobandegani, Irina Rish, Thomas R. Shultz |
| 2023 | ICASSP | Dialogue System with Missing Observation. | Djallel Bouneffouf, Mayank Agarwal, Irina Rish |
| 2023 | ICLR | Broken Neural Scaling Laws. | Ethan Caballero, Kshitij Gupta, Irina Rish, David Krueger |
| 2022 | CogSci | Cognitive Models as Simulators: The Case of Moral Decision-Making. | Ardavan Salehi Nobandegani, Thomas R. Shultz, Irina Rish |
| 2022 | CVPR | Parametric Scattering Networks. | Shanel Gauthier, Benjamin Thrien, Laurent Alsne-Racicot, Muawiz Chaudhary, Irina Rish, Eugene Belilovsky, Michael Eickenberg, Guy Wolf |
| 2022 | ICASSP | A Remedy For Distributional Shifts Through Expected Domain Translation. | Jean-Christophe Gagnon-Audet, Soroosh Shahtalebi, Frank Rudzicz, Irina Rish |
| 2022 | ICLR | Compositional Attention: Disentangling Search and Retrieval. | Sarthak Mittal, Sharath Chandra Raparthy, Irina Rish, Yoshua Bengio, Guillaume Lajoie |
| 2022 | ICML | Towards Scaling Difference Target Propagation by Learning Backprop Targets. | Maxence Ernoult, Fabrice Normandin, Abhinav Moudgil, Sean Spinney, Eugene Belilovsky, Irina Rish, Blake A. Richards, Yoshua Bengio |
| 2021 | ICASSP | Toward Skills Dialog Orchestration with Online Learning. | Djallel Bouneffouf, Raphal Fraud, Sohini Upadhyay, Mayank Agarwal, Yasaman Khazaeni, Irina Rish |
| 2021 | ICASSP | Double-Linear Thompson Sampling for Context-Attentive Bandits. | Djallel Bouneffouf, Raphal Fraud, Sohini Upadhyay, Yasaman Khazaeni, Irina Rish |
| 2021 | ICLR | Predicting Infectiousness for Proactive Contact Tracing. | Yoshua Bengio, Prateek Gupta, Tegan Maharaj, Nasim Rahaman, Martin Weiss, Tristan Deleu, Eilif Benjamin Mller, Meng Qu, Victor Schmidt, Pierre-Luc St-Charles, Hannah Alsdurf, Olexa Bilaniuk, David L. Buckeridge, Gatan Marceau-Caron, Pierre Luc Carrier, Joumana Ghosn, Satya Ortiz-Gagne, Christopher J. Pal, Irina Rish, Bernhard Schlkopf, Abhinav Sharma, Jian Tang, Andrew Williams |
| 2021 | IJCAI | Toward Optimal Solution for the Context-Attentive Bandit Problem. | Djallel Bouneffouf, Raphal Fraud, Sohini Upadhyay, Irina Rish, Yasaman Khazaeni |
| 2020 | AAAI | Modeling Dialogues with Hashcode Representations: A Nonparametric Approach. | Sahil Garg, Irina Rish, Guillermo A. Cecchi, Palash Goyal, Sarik Ghazarian, Shuyang Gao, Greg Ver Steeg, Aram Galstyan |
| 2020 | CEC | Survey on Applications of Multi-Armed and Contextual Bandits. | Djallel Bouneffouf, Irina Rish, Charu C. Aggarwal |
| 2020 | IJCAI | Models of Human Behavioral Agents in Bandits, Contextual Bandits and RL. | Baihan Lin, Guillermo A. Cecchi, Djallel Bouneffouf, Jenna M. Reinen, Irina Rish |
| 2019 | AAAI | Kernelized Hashcode Representations for Relation Extraction. | Sahil Garg, Aram Galstyan, Greg Ver Steeg, Irina Rish, Guillermo A. Cecchi, Shuyang Gao |
| 2019 | ICLR | Learning to Learn without Forgetting by Maximizing Transfer and Minimizing Interference. | Matthew Riemer, Ignacio Cases, Robert Ajemian, Miao Liu, Irina Rish, Yuhai Tu, Gerald Tesauro |
| 2019 | ICML | Beyond Backprop: Online Alternating Minimization with Auxiliary Variables. | Anna Choromanska, Benjamin Cowen, Sadhana Kumaravel, Ronny Luss, Mattia Rigotti, Irina Rish, Paolo Diachille, Viatcheslav Gurev, Brian Kingsbury, Ravi Tejwani, Djallel Bouneffouf |
| 2018 | ICDM | Contextual Bandit with Adaptive Feature Extraction. | Baihan Lin, Djallel Bouneffouf, Guillermo A. Cecchi, Irina Rish |
| 2018 | IJCAI | Dialogue Modeling Via Hash Functions. | Sahil Garg, Guillermo A. Cecchi, Irina Rish, Shuyang Gao, Greg Ver Steeg, Sarik Ghazarian, Palash Goyal, Aram Galstyan |
| 2017 | ICLR | Neurogenesis-Inspired Dictionary Learning: Online Model Adaption in a Changing World. | Sahil Garg, Irina Rish, Guillermo A. Cecchi, Aurlie C. Lozano |
| 2017 | IJCAI | Context Attentive Bandits: Contextual Bandit with Restricted Context. | Djallel Bouneffouf, Irina Rish, Guillermo A. Cecchi, Raphal Fraud |
| 2017 | IJCAI | Neurogenesis-Inspired Dictionary Learning: Online Model Adaption in a Changing World. | Sahil Garg, Irina Rish, Guillermo A. Cecchi, Aurlie C. Lozano |
| 2014 | SDM | Transductive HSIC Lasso. | Dan He, Irina Rish, Laxmi Parida |
| 2010 | ISAIM | Sparse Markov net learning with priors on regularization parameters. | Katya Scheinberg, Irina Rish, Narges Bani Asadi |
| 2009 | ICASSP | Map approach to learning sparse Gaussian Markov networks. | Narges Bani Asadi, Irina Rish, Katya Scheinberg, Dimitri Kanevsky, Bhuvana Ramabhadran |
| 2008 | ICML | Closed-form supervised dimensionality reduction with generalized linear models. | Irina Rish, Genady Grabarnik, Guillermo A. Cecchi, Francisco Pereira, Geoffrey J. Gordon |
| 2008 | ISAIM | Active Collaborative Prediction with Maximum Margin Matrix Factorization. | Irina Rish, Gerald Tesauro |
| 2007 | IM | Estimating End-to-End Performance by Collaborative Prediction with Active Sampling. | Irina Rish, Gerald Tesauro |
| 2007 | IMC | Blind source separation approach to performance diagnosis and dependency discovery. | Gaurav Chandalia, Irina Rish |
| 2007 | MASS | Empirical Study of Topology Effects on Diagnosis in Computer Networks. | Natalia Odintsova, Irina Rish |
| 2005 | IM | Test-based diagnosis: tree and matrix representations. | Alina Beygelzimer, Mark Brodie, Sheng Ma, Irina Rish |
| 2005 | UAI | Efficient Test Selection in Active Diagnosis via Entropy Approximation. | Alice X. Zheng, Irina Rish, Alina Beygelzimer |
| 2005 | SDM | Statictical Models for Unequally Spaced Time Series. | Alina Beygelzimer, Emre Erdogan, Sheng Ma, Irina Rish |
| 2004 | NOMS | Real-time problem determination in distributed systems using active probing. | Irina Rish, Mark Brodie, Natalia Odintsova, Sheng Ma, Genady Grabarnik |
| 2003 | IJCAI | Active Probing Strategies for Problem Diagnosis in Distributed Systems. | Mark Brodie, Irina Rish, Sheng Ma, Natalia Odintsova |
| 2003 | KDD | Critical event prediction for proactive management in large-scale computer clusters. | Ramendra K. Sahoo, Adam J. Oliner, Irina Rish, Manish Gupta, Jos E. Moreira, Sheng Ma, Ricardo Vilalta, Anand Sivasubramaniam |
| 2002 | AAAI | Accuracy vs. Efficiency Trade-offs in Probabilistic Diagnosis. | Irina Rish, Mark Brodie, Sheng Ma |
| 2002 | KR | Inference Complexity as a Model-Selection Criterion for Learning Bayesian Networks. | Alina Beygelzimer, Irina Rish |
| 2000 | AAAI | Recognizing End-User Transactions in Performance Management. | Joseph L. Hellerstein, T. S. Jayram, Irina Rish |
| 1998 | UAI | Empirical Evaluation of Approximation Algorithms for Probabilistic Decoding. | Irina Rish, Kalev Kask, Rina Dechter |
| 1997 | AAAI | Summarizing CSP Hardness with Continuous Probability Distributions. | Daniel Frost, Irina Rish, Llus Vila |
| 1997 | CP | Statistical Analysis of Backtracking on Inconsistent CSPs. | Irina Rish, Daniel Frost |
| 1997 | UAI | A Scheme for Approximating Probabilistic Inference. | Rina Dechter, Irina Rish |
| 1996 | CP | To Guess or to Think? Hybrid Algorithms for SAT (Extended Abstract). | Irina Rish, Rina Dechter |
| 1994 | KR | Directional Resolution: The Davis-Putnam Procedure, Revisited. | Rina Dechter, Irina Rish |