Efficient Multimodal Question Answering (EMM-QA)

How to get there: From the registration desk on the ground floor, follow the hallway to the Auditorium, then take the escalator inside the Auditorium to the second floor.
EMM-QA is an ICML 2026 workshop focused on question answering systems that must balance accuracy, efficiency, and adaptability across multiple input modalities. The workshop brings together researchers from academia and industry working on knowledge-intensive multimodal systems that operate under practical resource constraints.
Rather than focusing only on larger models, the workshop emphasizes methods that make multimodal question answering usable in real settings, including retrieval-augmented systems, compact models, efficient inference, and human-in-the-loop evaluation.
ANNOUNCEMENTS
π The exact Contributed Paper Spotlight Schedule is now available.π List of Accepted Papers and Shared Challenge Papers is now available! β οΈ Virtual poster presentations are also available here under βΆοΈ icon!
π Check Accepted Papers, Poster Sessions and Board Assignments section at the bottom of this page to find your poster ID, session, and board number in Hall A.
π Workshop Schedule is now available.
π Call for Papers
π Computer Teams
π Join the community on Discord.
Scope
The workshop is centered on efficient multimodal question answering. It also welcomes closely related work on multimodal retrieval, reasoning, evaluation, benchmarking, and efficient inference when those contributions are clearly connected to question answering or other knowledge-intensive multimodal tasks.
Like the previous iteration of EfficientQA, which focused on text-only question answering, we will also host a human-computer question answering competition. If youβd like to take part in that part of the competition (it should be fun!), you can either play as a team or write questions.
Workshop Format
The workshop is planned as a one-day event combining:
- Contributed papers
- Poster presentations
- Invited keynotes
- Shared-task highlights
- A live human-computer question answering event
The workshop will also serve as the venue where we announce the winning systems from the QANTA 2026 computer competition.
Schedule
- Workshop takes place on July 11th. Both poster sessions
- All talk sessions (invited talks, spotlights, challenge talks, awards, etc.) will take place in the ASEM Ballroom 201 at COEX.
- All poster sessions will take place separately in Hall A, poster boards 1612β1617, 1700β1711, outside the workshop room area at COEX. You can review the Hall A plan here.
| Time | Activity | Duration |
|---|---|---|
| 08:00β08:10 | Welcome & Workshop Overview | 10 min |
| 08:10β08:50 | π¦ Naman Goyal & Jenny Ni: Multimodal Robustness Under Distribution Shift | 40 min |
| 08:50β09:00 | Q&A | 10 min |
| 09:00β09:15 | β Coffee Break | 15 min |
| 09:15β09:55 | π¦ Sewon Min: PIXELRAG: Web Screenshots Beat Text for Retrieval-Augmented Generation | 40 min |
| 09:55β10:05 | Q&A | 10 min |
| 10:05β10:50 | π¨ Contributed Paper Spotlights I | 45 min |
| 10:05β10:15 | π¨ Mirage Probes: How Vision Models Fake Visual Understanding β Daniel Ben-Levi et al. | 10 min |
| 10:16β10:26 | π¨ VLMs Trace Without Tracking: Diagnosing Failures in Visual Path Following β Hyesoo Hong et al. | 10 min |
| 10:27β10:37 | π¨ DistortBench: Benchmarking Vision Language Models on Image Distortion Identification β Divyanshu Goyal et al. | 10 min |
| 10:38β10:48 | π¨ CCDiff: Inverse Canonical Correlation Analysis for Discovering Visual Differences in Natural Language (Virtual) β Neelesh Bisht et al. | 10 min |
| 10:50β11:50 | π§ Workshop Posters I | 60 min |
| 11:50β12:50 | Lunch | 60 min |
| 12:50β13:20 | π€ Live AI QA Competition | 30 min |
| 13:20β14:00 | π¦ Mrinmaya Sachan: Behavioral Shortcuts and Cross-Modal Alignment Failures of Multimodal Large Language Models | 40 min |
| 14:00β14:10 | Q&A | 10 min |
| 14:10β14:50 | π¦ Robin Jia: The Golden Age of Adversarial Evaluation | 40 min |
| 14:50β15:00 | Q&A | 10 min |
| 15:00β15:15 | β Coffee Break | 15 min |
| 15:15β15:35 | Shared Challenge Introduction & Results Overview | 20 min |
| 15:35β15:55 | π¨ Contributed Paper Spotlights II | 20 min |
| 15:35β15:45 | π¨ Stop Thinking, Start Looking: Efficient Post-Training for Multimodal Document Question Answering via Reasoning-Free Alignment β Harikrishnan Puthan Madathil et al. | 10 min |
| 15:45β15:55 | π¨ FAGER: Factually Grounded Evaluation and Refinement of Text-to-Image Models (Virtual) β Youngsun Lim et al. | 10 min |
| 15:55β16:05 | π Challenge Awards | 10 min |
| 16:05β16:10 | Closing Remarks | 5 min |
| 16:10β17:00 | π§ Workshop Posters II + Shared Challenge Posters | 50 min |
Legend
- π¦ Invited Talks
- π¨ Contributed Paper Spotlights / Best Challenge Team Talk
- π§ Poster Sessions
Confirmed Keynote Speakers
- Sewon Min (UC Berkeley EECS & Allen Institute for AI)
- Mrinmaya Sachan (ETH ZΓΌrich)
- Robin Jia (University of Southern California)
- Naman Goyal (Google DeepMind) & Jenny Ni (Google)
Organizers
- Jordan Boyd-Graber, University of Maryland
- Martin FajΔΓk, Brno University of Technology
- George Jojo Boateng, ETH Zurich / Kwame AI
- Ikuya Yamada, Studio Ousia / Tohoku University / Nagoya University / RIKEN
- Chen Zhao, NYU Shanghai
Contact
Questions about the workshop can be sent to emm-qa-organizers@googlegroups.com. Or join the Discord.
Accepted Papers, Poster Sessions and Board Assignments
πΊοΈ The plan of the Hall A is here.
| Poster ID | Session | Board | Topic | Paper | Authors |
|---|---|---|---|---|---|
| P01 | 1 | 1612 | Multimodal Retrieval QA | Scaling Down: Multi-Hop Information Retrieval in Resource-Constrained Environments | Nikolay Staroverov |
| P02 | 1 | 1612 | Multimodal Retrieval QA | Latent Abstraction for Retrieval-Augmented Generation | Ha-Lan Nguyen; Nguyen A Minh; Dung D. Le |
| P03 | 1 | 1613 | Multimodal Retrieval QA | Salient Knowledge Pathways: Sparse Cross-Modal Routing for Efficient Knowledge-Intensive Multimodal Question Answering | Noor Islam S. Mohammad |
| P04 | 1 | 1613 | Multimodal Retrieval QA | Visual Evidence Collapse as the Missing Signal in Adaptive Multimodal Retrieval: A Position | GΓΆktuΔ AslanoΔlu |
| P05 | 1 | 1614 | Multimodal Retrieval QA | Look Before You Zoom: Adaptive Routing for the Resolution-Context Trade-off in Visual RAG | Oanh N Tran; Thanh Quoc Hung Le; Oscar Chew; Kuan-Hao Huang; Khoa Doan |
| P06 | 1 | 1614 | Multimodal Retrieval QA | PixelRAG: Retrieval and Reading in Pixel Space over Millions of Web Screenshots | Yichuan Wang; Zhifei Li; Zirui Wang; Paul Teiletche; Lesheng Jin; Matei Zaharia; Joseph E Gonzalez; Sewon Min |
| P07 | 1 | 1615 | Multimodal Retrieval QA | Read or Look? Textification Safety Boundaries for Efficient Multimodal Document QA | Pan Xie |
| P08 | 1 | 1615 | Multimodal Retrieval QA | What Do Chart Question Answering Benchmarks Measure? Task-Specific Visual Dependence in Efficient Multimodal QA | Mary Le |
| P09 | 1 | 1616 | Visual Token Efficiency | One Token per Multimodal Evidence: Latent Memory for Resource-Constrained QA | Zhi Zheng; Ziqiao Meng; Hao Luan; Wei Liu; Wee Sun Lee |
| P10 | 1 | 1616 | Visual Token Efficiency | A Picture is Worth a Thousand Tokens: A Practitionerβs Guide to Visual Token Compression | Vipul Joshi; Vikash Sharma; Amir Raza; Peyush Jain; Mayank Jauhari; Anurag Tripathi |
| P11 | 1 | 1617 | Visual Token Efficiency | Efficient Visual Token Compression for 3D Question Answering | Changwoo Baek; Kyeongbo Kong |
| P12 | 1 | 1617 | Visual Token Efficiency | LARE: Low-Attention Region Encoding for TextβImage Retrieval | Muhammad K Khan; Abdulmalik Alquwayfili; Faisal AlMeshal; Jumanah Almajnouni; Leena Alotaibi; Huda A Alamri; Raied Aljadaany; Faisal alhajari; Alreem Almuhrij; Mohammed Alkhrashi; Abdullah Aldwyish |
| P13 | 1 | 1700 | Data-Efficient QA | Stop Thinking, Start Looking: Efficient Post-Training for Multimodal Document Question Answering via Reasoning-Free Alignment | HARIKRISHNAN PUTHAN MADATHIL; Goutham Vignesh; Ganesh Parab; Saisubramaniam Gopalakrishnan; Vishal Vaddina; Varun V; Rohit Agrawal |
| P14 | 1 | 1700 | Data-Efficient QA | Data-Efficient Curation for Multimodal Reasoning under Fixed Training Protocols | Yosub Shin; Michael Buriek; Boris Sobolev; Pavel Bushuyeu; Vikas Kumar; Samuel Watson; Haoyang Xu; Igor Molybog |
| P15 | 1 | 1701 | Confidence and Abstention | Confidence-Aware Incremental Multimodal QA with Early Exit Reasoning | Kaustubha V; Shravan K; Harini S |
| P16 | 1 | 1701 | Confidence and Abstention | Calibrated Confidence Is Hard to Beat: A Negative Result on Evidence-Accumulation Buzzing for Zero-Shot Incremental Question Answering | Arihant Jain |
| P17 | 1 | 1702 | Confidence and Abstention | Cheap When Confident: The Per-Model Limits of Selective Answering in Multimodal Geometry QA | Vipra Bindal |
| P18 | 1 | 1702 | Confidence and Abstention | Context-Aware Conformal Prediction for VLM-Based Driving Scene QA | Yang-Jun Joo; Younggun Kim; Sung-Yeon Park; Mohamed Abdel-Aty |
| P19 | 1 | 1703 | Medical QA | Answer, Clarify, or Abstain: Fine-Grained Selective Prediction for Medical VLMs | Duy A Nguyen; Tuan T Nguyen; Minh Do; Khoa Doan |
| P20 | 1 | 1703 | Medical QA | Efficient Multimodal Clinical Question Answering for Pulmonary Embolism Risk Assessment | Xiangyuan Xue; Yang Yu; Yan Gao; Junyan Wang; Bin Chen; Lingyan Ruan; Ting Dang; Hong Jia |
| P21 | 1 | 1704 | Medical QA | Iterative Multimodal Retrieval-Augmented Generation for Medical Question Answering | Xupeng Chen; Binbin Shi; Chenqian Le; Jiaqi Zhang; Kewen Wang; Ran Gong; Jinhan Zhang; Chihang Wang |
| P22 | 1 | 1704 | Medical QA | Pocket-Dentist: Efficient Multimodal QA for On-Device Dental Image Understanding | Kai Bian; Xucheng Guo; Lingyan Ruan; Bin Chen; Yiran Shen; Ting Dang; Hong Jia |
| P23 | 1 | 1705 | Missing Modality QA | Recovering a Missing Modality in Multimodal QA via Low-Rank Completion | Jing Wang; Huan Xu; Jie Shen |
| P24 | 2 | 1612 | VLM Robustness Benchmarks | DistortBench: Benchmarking Vision Language Models on Image Distortion Identification | Divyanshu Goyal; Akhil Eppa; Vanya Bannihatti Kumar |
| P25 | 2 | 1612 | VLM Robustness Benchmarks | AMVICC: A Novel Benchmark for Cross-Modal Failure Mode Profiling for VLMs and IGMs | Pranay Goel; Aahana Basappa; Anusri Karra; Anish Karra; Kevin Zhu |
| P26 | 2 | 1613 | VLM Robustness Benchmarks | VLMs Trace Without Tracking: Diagnosing Failures in Visual Path Following | Hyesoo Hong; Min Soo Kim; Wonje Jeung; Sangyeon Yoon; Dongjae Jeon; Albert No |
| P27 | 2 | 1613 | VLM Failure Analysis | Pop-Up Distractions Reveal Bag-of-Events Behavior in Video Large Language Models | Oscar Chew; Serhii Honcharenko; Qian-Hui Chen; Patricia Lu; Dishant P Zaveri; Khoa Doan; Kuan-Hao Huang |
| P28 | 2 | 1614 | VLM Failure Analysis | Detection-Guided Attention Steering for Vision Language Models | Alan W Zhang; Rui Pan; Mike Wong; Ravi Netravali |
| P29 | 2 | 1614 | VLM Failure Analysis | Mirage Probes: Selective Construction of False Images in Vision Language Model Inference | Daniel Ben-Levi; Judah A Goldfeder; Weiliang Zhao; Raz Lapid; Amit LeVi; Allen Roush; Ravid Shwartz-Ziv; Hod Lipson |
| P30 | 2 | 1615 | Temporal Multimodal Understanding | WorldMemArena: Evaluating Multimodal Agent Memory Through ActionβWorld Interaction | Chengzhi Liu; Yuzhe YANG; Sophia X Pu; Yepeng Liu; Lin Long; Yichen Guo; Nuo Chen; zhaotian Weng; yiheng zhong; Angxiao Zong; Elena Kochkina; Simerjot Kaur; Charese Smiley; Xiaomo Liu; James Zou; Sheng Liu; Yuheng Bu; Songyou Peng; Xin (Eric) Wang |
| P31 | 2 | 1615 | Temporal Multimodal Understanding | Multimodal Hidden Markov Models for Persistent Emotional State Tracking | Anamika Ragu; Aneesh Jonelagadda |
| P32 | 2 | 1616 | Temporal Multimodal Understanding | Augmenting Video Models with Pose Tokens for Human-Centric Understanding | Isabella Zhu; Stella Su; David Dai; Paul Pu Liang |
| P33 | 2 | 1616 | Generative Media Detection | Position: Efficient Dual-View AI-Generated Video Detection Needs a Visual-Language Dual View | Dylan Xinming Hou; Juntian Zhang; Xu Gu; Yichen WU; Nils Lukas; Gus xia; Xiuying Chen; Yuhan Liu |
| P34 | 2 | 1617 | Text-to-Image Evaluation | FAGER: Factually Grounded Evaluation and Refinement of Text-to-Image Models | Youngsun Lim; Cusuh Ham; Pin-Yu Chen; Deepti Ghadiyaram |
| P35 | 2 | 1617 | Text-to-Image Evaluation | CCDiff: Inverse Canonical Correlation Analysis for Discovering Visual Differences in Natural Language | Neelesh Bisht; Xingjian Li; Zihan Li; Bo Jiang; RUNMIN JIANG; Mostofa Rafid Uddin; Yang Liu; Min Xu |
| P36 | 2 | 1700 | Multimodal Generation Tools | MMDiff: Multimodal Model Diffing for Feature Discovery and Control | Lachin Naghashyar; Hunar Batra; Ashkan Khakzar; Phil Torr; Ronald Clark; Christian Schroeder de Witt; Constantin Venhoff |
| P37 | 2 | 1700 | Multimodal Generation Tools | Any2Poster: Any-Source Poster Generation Across Modalities and Domains | Amogh Vinaykumar; Suozhi Huang; Aiden Y Li; Shilong Liu |
| P38 | 2 | 1701 | Multimodal Generation Tools | From Synopsis to Storyboard: Enhancing Prompt Expressiveness for Multi-shot Video Generation | Xu Gu; Yuhan Liu; Wei Ji; Ruihua Song; Roger Zimmermann |
| P39 | 2 | 1701 | Reasoning Evaluation | Auditable Step Verification for Vision-Language Reasoning | Shervin Ghasemlou |
| P40 | 2 | 1702 | Reasoning Evaluation | Does Verbose Chain-of-Thought Really Help? A Dual-Validator Replication and Mechanistic Analysis | Wenlong Wang; Fergal Reid |
| P41 | 2 | 1702 | Reasoning Evaluation | The Shape of Overthinking: Backtracking Bursts in Long Reasoning Traces | Navid Rezazadeh; Arash Gholamidavoodi |
| P42 | 2 | 1703 | Reasoning Evaluation | Can LLMs Reconstruct Why an Answer Is Correct? A Step-Level Evaluation of Answer-Conditioned Reasoning | Lei Sun |
| P43 | 2 | 1703 | Reasoning Evaluation | Coherence Under Commitment: Probing Generalization and Vacuous Memorization in LLM Logical Reasoning | Noor Islam S. Mohammad; Mahmudul Hasan |
| P44 | 2 | 1704 | Model Alignment | Co-LoRA: Collaborative Model Personalization on Heterogeneous Multi-Modal Clients | Minhyuk Seo; Taeheon Kim; Hankook Lee; Jonghyun Choi; Tinne Tuytelaars |
| P45 | 2 | 1704 | Model Alignment | SOTAlign: Semi-Supervised Alignment of Unimodal Vision and Language Models via Optimal Transport | Simon Roschmann; Paul KRZAKALA; Sonia Mazelet; Quentin Bouniot; Zeynep Akata |
Sponsors/Acknowledgements
- This workshop is partially supported by Horizon EU programme through project ELOQUENCE, grant no. 101135916.