Elias Stengel-Eskin

According to our database, Elias Stengel-Eskin authored at least 61 papers between 2017 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

RotBench: Evaluating Multimodal Large Language Models on Identifying Image Rotation.

Tianyi Niu, Jaemin Cho, Elias Stengel-Eskin, Mohit Bansal

CoRR, August, 2025

GrAInS: Gradient-based Attribution for Inference-Time Steering of LLMs and VLMs.

Duy Nguyen, Archiki Prasad, Elias Stengel-Eskin, Mohit Bansal

CoRR, July, 2025

Context-Informed Grounding Supervision.

Hyunji Lee, Seunghyun Yoon, Yunjae Won, Hanseok Oh, Geewook Kim, Trung Bui, Franck Dernoncourt, Elias Stengel-Eskin, Mohit Bansal, Minjoon Seo

CoRR, June, 2025

GenerationPrograms: Fine-grained Attribution with Executable Programs.

David Wan, Eran Hirsch, Elias Stengel-Eskin, Ido Dagan, Mohit Bansal

CoRR, June, 2025

Movie Facts and Fibs (MF²): A Benchmark for Long Movie Understanding.

Emmanouil Zaranis, António Farinhas, Saul José Rodrigues dos Santos, Beatriz Canaverde, Miguel Moura Ramos, Aditya K. Surikuchi, André Viveiros, Baohao Liao, Elena Belén Bueno-Benito, Nithin Sivakumaran, Pavlo Vasylenko, Shoubin Yu, Sonal Sannigrahi, Wafaa Mohammed, Ben Peters, Danae Sánchez Villegas, Elias Stengel-Eskin, Giuseppe Attanasio, Jaehong Yoon, Stella Frank, Alessandro Suglia, Chrysoula Zerva, Desmond Elliott, Mariella Dimiccoli, Mohit Bansal, Oswald Lanz, Raffaella Bernardi, Raquel Fernández, Sandro Pezzelle, Vlad Niculae, André F. T. Martins

CoRR, June, 2025

CLaMR: Contextualized Late-Interaction for Multimodal Content Retrieval.

David Wan, Han Wang, Elias Stengel-Eskin, Jaemin Cho, Mohit Bansal

CoRR, June, 2025

CLATTER: Comprehensive Entailment Reasoning for Hallucination Detection.

Ron Eliav, Arie Cattan, Eran Hirsch, Shahaf Bassan, Elias Stengel-Eskin, Mohit Bansal, Ido Dagan

CoRR, June, 2025

CAPTURe: Evaluating Spatial Reasoning in Vision Language Models via Occluded Object Counting.

Atin Pothiraj, Elias Stengel-Eskin, Jaemin Cho, Mohit Bansal

CoRR, April, 2025

Retrieval-Augmented Generation with Conflicting Evidence.

Han Wang, Archiki Prasad, Elias Stengel-Eskin, Mohit Bansal

CoRR, April, 2025

Executable Functional Abstractions: Inferring Generative Programs for Advanced Math Problems.

Zaid Khan, Elias Stengel-Eskin, Archiki Prasad, Jaemin Cho, Mohit Bansal

CoRR, April, 2025

Task-Circuit Quantization: Leveraging Knowledge Localization and Interpretability for Compression.

Hanqi Xiao, Yi-Lin Sung, Elias Stengel-Eskin, Mohit Bansal

CoRR, April, 2025

Symbolic Mixture-of-Experts: Adaptive Skill-based Routing for Heterogeneous Reasoning.

Justin Chih-Yao Chen, Sukwon Yun, Elias Stengel-Eskin, Tianlong Chen, Mohit Bansal

CoRR, March, 2025

UPCORE: Utility-Preserving Coreset Selection for Balanced Unlearning.

Vaidehi Patil, Elias Stengel-Eskin, Mohit Bansal

CoRR, February, 2025

On the Trustworthiness of Generative Foundation Models: Guideline, Assessment, and Perspective.

Yue Huang, Chujie Gao, Siyuan Wu, Haoran Wang, Xiangqi Wang, Yujun Zhou, Yanbo Wang, Jiayi Ye, Jiawen Shi, Qihui Zhang, Yuan Li, Han Bao, Zhaoyi Liu, Tianrui Guan, Dongping Chen, Ruoxi Chen, Kehan Guo, Andy Zou, Bryan Hooi Kuen-Yew, Caiming Xiong, Elias Stengel-Eskin, Hongyang Zhang, Hongzhi Yin, Huan Zhang, Huaxiu Yao, Jaehong Yoon, Jieyu Zhang, Kai Shu, Kaijie Zhu, Ranjay Krishna, Swabha Swayamdipta, Taiwei Shi, Weijia Shi, Xiang Li, Yiwei Li, Yuexing Hao, Zhihao Jia, Zhize Li, Xiuying Chen, Zhengzhong Tu, Xiyang Hu, Tianyi Zhou, Jieyu Zhao, Lichao Sun, Furong Huang, Or Cohen Sasson, Prasanna Sattigeri, Anka Reuel, Max Lamparth, Yue Zhao, Nouha Dziri, Yu Su, Huan Sun, Heng Ji, Chaowei Xiao, Mohit Bansal, Nitesh V. Chawla, Jian Pei, Jianfeng Gao, Michael Backes, Philip S. Yu, Neil Zhenqiang Gong, Pin-Yu Chen, Bo Li, Xiangliang Zhang

CoRR, February, 2025

Learning to Generate Unit Tests for Automated Debugging.

Archiki Prasad, Elias Stengel-Eskin, Justin Chih-Yao Chen, Zaid Khan, Mohit Bansal

CoRR, February, 2025

AdaCAD: Adaptively Decoding to Balance Conflicts between Contextual and Parametric Knowledge.

Han Wang, Archiki Prasad, Elias Stengel-Eskin, Mohit Bansal

Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025

MAMM-Refine: A Recipe for Improving Faithfulness in Generation with Multi-Agent Collaboration.

David Wan, Justin Chih-Yao Chen, Elias Stengel-Eskin, Mohit Bansal

Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025

Teaching Models to Balance Resisting and Accepting Persuasion.

Elias Stengel-Eskin, Peter Hase, Mohit Bansal

Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025

System 1.x: Learning to Balance Fast and Slow Planning with Language Models.

Swarnadeep Saha, Archiki Prasad, Justin Chih-Yao Chen, Peter Hase, Elias Stengel-Eskin, Mohit Bansal

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

See It from My Perspective: How Language Affects Cultural Bias in Image Understanding.

Amith Ananthram, Elias Stengel-Eskin, Mohit Bansal, Kathleen McKeown

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

DataEnvGym: Data Generation Agents in Teacher Environments with Student Feedback.

Zaid Khan, Elias Stengel-Eskin, Jaemin Cho, Mohit Bansal

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

VideoTree: Adaptive Tree-based Video Representation for LLM Reasoning on Long Videos.

Ziyang Wang, Shoubin Yu, Elias Stengel-Eskin, Jaehong Yoon, Feng Cheng, Gedas Bertasius, Mohit Bansal

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

Multi-Attribute Steering of Language Models via Targeted Intervention.

Duy Nguyen, Archiki Prasad, Elias Stengel-Eskin, Mohit Bansal

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

LAQuer: Localized Attribution Queries in Content-grounded Generation.

Eran Hirsch, Aviv Slobodkin, David Wan, Elias Stengel-Eskin, Mohit Bansal, Ido Dagan

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024

Fundamental Problems With Model Editing: How Should Rational Belief Revision Work in LLMs?

Peter Hase, Thomas Hofweber, Xiang Zhou, Elias Stengel-Eskin, Mohit Bansal

Trans. Mach. Learn. Res., 2024

LASeR: Learning to Adaptively Select Reward Models with Multi-Armed Bandits.

Duy Nguyen, Archiki Prasad, Elias Stengel-Eskin, Mohit Bansal

CoRR, 2024

MAgICoRe: Multi-Agent, Iterative, Coarse-to-Fine Refinement for Reasoning.

Justin Chih-Yao Chen, Archiki Prasad, Swarnadeep Saha, Elias Stengel-Eskin, Mohit Bansal

CoRR, 2024

See It from My Perspective: Diagnosing the Western Cultural Bias of Large Vision-Language Models in Image Understanding.

Amith Ananthram, Elias Stengel-Eskin, Carl Vondrick, Mohit Bansal, Kathleen R. McKeown

CoRR, 2024

Are language models rational? The case of coherence norms and belief revision.

Thomas Hofweber, Peter Hase, Elias Stengel-Eskin, Mohit Bansal

CoRR, 2024

LACIE: Listener-Aware Finetuning for Confidence Calibration in Large Language Models.

Elias Stengel-Eskin, Peter Hase, Mohit Bansal

CoRR, 2024

Soft Self-Consistency Improves Language Model Agents.

Han Wang, Archiki Prasad, Elias Stengel-Eskin, Mohit Bansal

CoRR, 2024

GTBench: Uncovering the Strategic Reasoning Limitations of LLMs via Game-Theoretic Evaluations.

Jinhao Duan, Renming Zhang, James Diffenderfer, Bhavya Kailkhura, Lichao Sun, Elias Stengel-Eskin, Mohit Bansal, Tianlong Chen, Kaidi Xu

CoRR, 2024

LACIE: Listener-Aware Finetuning for Calibration in Large Language Models.

Elias Stengel-Eskin, Peter Hase, Mohit Bansal

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

GTBench: Uncovering the Strategic Reasoning Capabilities of LLMs via Game-Theoretic Evaluations.

Jinhao Duan, Renming Zhang, James Diffenderfer, Bhavya Kailkhura, Lichao Sun, Elias Stengel-Eskin, Mohit Bansal, Tianlong Chen, Kaidi Xu

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

MIRACLE: An Online, Explainable Multimodal Interactive Concept Learning System.

Ansel Blume, Khanh Duy Nguyen, Zhenhailong Wang, Yangyi Chen, Michal Shlapentokh-Rothman, Xiaomeng Jin, Jeonghwan Kim, Zhen Zhu, Jiateng Liu, Kuan-Hao Huang, Mankeerat Sidhu, Xuanming Zhang, Vivian Liu, Raunak Sinha, Te-Lin Wu, Abhay Zala, Elias Stengel-Eskin, Da Yin, Yao Xiao, Utkarsh Mall, Zhou Yu, Kai-Wei Chang, Camille Cobb, Karrie Karahalios, Lydia B. Chilton, Mohit Bansal, Nanyun Peng, Carl Vondrick, Derek Hoiem, Heng Ji

Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024

ReGAL: Refactoring Programs to Discover Generalizable Abstractions.

Elias Stengel-Eskin, Archiki Prasad, Mohit Bansal

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Language-guided Skill Learning with Temporal Variational Inference.

Haotian Fu, Pratyusha Sharma, Elias Stengel-Eskin, George Konidaris, Nicolas Le Roux, Marc-Alexandre Côté, Xingdi Yuan

Proceedings of the Forty-first International Conference on Machine Learning, 2024

MAGDi: Structured Distillation of Multi-Agent Interaction Graphs Improves Reasoning in Smaller Language Models.

Justin Chih-Yao Chen, Swarnadeep Saha, Elias Stengel-Eskin, Mohit Bansal

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Zero and Few-shot Semantic Parsing with Ambiguous Inputs.

Elias Stengel-Eskin, Kyle Rawlins, Benjamin Van Durme

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Rephrase, Augment, Reason: Visual Grounding of Questions for Vision-Language Models.

Archiki Prasad, Elias Stengel-Eskin, Mohit Bansal

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Contrastive Region Guidance: Improving Grounding in Vision-Language Models Without Training.

David Wan, Jaemin Cho, Elias Stengel-Eskin, Mohit Bansal

Proceedings of the Computer Vision - ECCV 2024, 2024

Sub-goal Distillation: A Method to Improve Small Language Agents.

Maryam Hashemzadeh, Elias Stengel-Eskin, Sarath Chandar, Marc-Alexandre Côté

Proceedings of the Conference on Lifelong Learning Agents, 2024

Soft Self-Consistency Improves Language Models Agents.

Han Wang, Archiki Prasad, Elias Stengel-Eskin, Mohit Bansal

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics, 2024

2023

Calibrated Interpretation: Confidence Estimation in Semantic Parsing.

Elias Stengel-Eskin, Benjamin Van Durme

Trans. Assoc. Comput. Linguistics, 2023

Did You Mean...? Confidence-based Trade-offs in Semantic Parsing.

Elias Stengel-Eskin, Benjamin Van Durme

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Super-CLEVR: A Virtual Benchmark to Diagnose Domain Robustness in Visual Reasoning.

Zhuowan Li, Xingrui Wang, Elias Stengel-Eskin, Adam Kortylewski, Wufei Ma, Benjamin Van Durme, Alan L. Yuille

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Why Did the Chicken Cross the Road? Rephrasing and Analyzing Ambiguous Questions in VQA.

Elias Stengel-Eskin, Jimena Guallar-Blasco, Yi Zhou, Benjamin Van Durme

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022

Visual Commonsense in Pretrained Unimodal and Multimodal Models.

Chenyu Zhang, Benjamin Van Durme, Zhuowan Li, Elias Stengel-Eskin

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

When More Data Hurts: A Troubling Quirk in Developing Broad-Coverage Natural Language Understanding Systems.

Elias Stengel-Eskin, Emmanouil Antonios Platanios, Adam Pauls, Sam Thomson, Hao Fang, Benjamin Van Durme, Jason Eisner, Yu Su

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

The Curious Case of Control.

Elias Stengel-Eskin, Benjamin Van Durme

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

2021

Joint Universal Syntactic and Semantic Parsing.

Elias Stengel-Eskin, Kenton W. Murray, Sheng Zhang, Aaron Steven White, Benjamin Van Durme

Trans. Assoc. Comput. Linguistics, 2021

Iterative Paraphrastic Augmentation with Discriminative Span Alignment.

Ryan Culkin, J. Edward Hu, Elias Stengel-Eskin, Guanghui Qin, Benjamin Van Durme

Trans. Assoc. Comput. Linguistics, 2021

Calibrating Concepts and Operations: Towards Symbolic Reasoning on Real Images.

Zhuowan Li, Elias Stengel-Eskin, Yixiao Zhang, Cihang Xie, Quan Tran, Benjamin Van Durme, Alan L. Yuille

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Guiding Multi-Step Rearrangement Tasks with Natural Language Instructions.

Elias Stengel-Eskin, Andrew Hundt, Zhuohong He, Aditya Murali, Nakul Gopalan, Matthew C. Gombolay, Gregory D. Hager

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

2020

The Universal Decompositional Semantics Dataset and Decomp Toolkit.

Aaron Steven White, Elias Stengel-Eskin, Siddharth Vashishtha, Venkata Subrahmanyan Govindarajan, Dee Ann Reisinger, Tim Vieira, Keisuke Sakaguchi, Sheng Zhang, Francis Ferraro, Rachel Rudinger, Kyle Rawlins, Benjamin Van Durme

Proceedings of The 12th Language Resources and Evaluation Conference, 2020

Universal Decompositional Semantic Parsing.

Elias Stengel-Eskin, Aaron Steven White, Sheng Zhang, Benjamin Van Durme

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019

Transductive Parsing for Universal Decompositional Semantics.

Elias Stengel-Eskin, Aaron Steven White, Sheng Zhang, Benjamin Van Durme

CoRR, 2019

NIST TAC SM-KBP 2019 System Description: JHU/UR Framework.

Yunmo Chen, Seth Ebner, Tongfei Chen, Patrick Xia, Elias Stengel-Eskin, Tzu-Ray Su, J. Edward Hu, Nils Holzenberger, Ryan Culkin, Craig Harman, Max Thomas, Thomas Lippincott, Aaron Steven White, Kyle Rawlins, Benjamin Van Durme

Proceedings of the 2019 Text Analysis Conference, 2019

A Discriminative Neural Model for Cross-Lingual Word Alignment.

Elias Stengel-Eskin, Tzu-Ray Su, Matt Post, Benjamin Van Durme

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

2018

NIST TAC SM-KBP 2018 System Description: JHU/UR Pipeline.

Patrick Xia, Elias Stengel-Eskin, Tongfei Chen, Seth Ebner, Nils Holzenberger, Ryan Culkin, Pushpendre Rastogi, Xutai Ma, Benjamin Van Durme

Proceedings of the 2018 Text Analysis Conference, 2018

2017

Polyglot and Speech Corpus Tools: A System for Representing, Integrating, and Querying Speech Corpora.

Michael McAuliffe, Elias Stengel-Eskin, Michaela Socolof, Morgan Sonderegger

Proceedings of the 18th Annual Conference of the International Speech Communication Association, 2017