2 citations · 9 across the 33 of their papers we have counts for
14 papers · 1 filter
Charts Are Not Images: On the Challenges of Scientific Chart Editing
Shawn Li, Ryan Rossi, Sungchul Kim +5
Generative models, such as diffusion and autoregressive approaches, have demonstrated impressive capabilities in editing natural images. However, applying these tools to scientific…
Structured Uncertainty guided Clarification for LLM Agents
Manan Suri, Puneet Mathur, Nedim Lipka +3
LLM agents with tool-calling capabilities often fail when user instructions are ambiguous or incomplete, leading to incorrect invocations and task failures. Existing approaches ope…
SQLSpace: A Representation Space for Text-to-SQL to Discover and Mitigate Robustness Gaps
Neha Srikanth, Victor Bursztyn, Puneet Mathur +1
We introduce SQLSpace, a human-interpretable, generalizable, compact representation for text-to-SQL examples derived with minimal human intervention. We demonstrate the utility of…
MLLM as a UI Judge: Benchmarking Multimodal LLMs for Predicting Human Perception of User Interfaces
Reuben A. Luera, Ryan Rossi, Franck Dernoncourt +12
In an ideal design pipeline, user interface (UI) design is intertwined with user research to validate decisions, yet studies are often resource-constrained during early exploration…
A Survey on Long-Video Storytelling Generation: Architectures, Consistency, and Cinematic Quality
Mohamed Elmoghany, Ryan Rossi, Seunghyun Yoon +26
Despite the significant progress that has been made in video generative models, existing state-of-the-art methods can only produce videos lasting 5-16 seconds, often labeled "long-…
Lizard: An Efficient Linearization Framework for Large Language Models
Chien Van Nguyen, Huy Nguyen, Ruiyi Zhang +10
We propose Lizard, a linearization framework that transforms pretrained Transformer-based Large Language Models (LLMs) into subquadratic architectures. Transformers faces severe co…
Follow the Flow: Fine-grained Flowchart Attribution with Neurosymbolic Agents
Manan Suri, Puneet Mathur, Nedim Lipka +4
Flowcharts are a critical tool for visualizing decision-making processes. However, their non-linear structure and complex visual-textual relationships make it challenging to interp…
ChartLens: Fine-grained Visual Attribution in Charts
Manan Suri, Puneet Mathur, Nedim Lipka +3
The growing capabilities of multimodal large language models (MLLMs) have advanced tasks like chart understanding. However, these models often suffer from hallucinations, where gen…
GraphicBench: A Planning Benchmark for Graphic Design with Language Agents
Dayeon Ki, Tianyi Zhou, Marine Carpuat +3
Large Language Model (LLM)-powered agents have unlocked new possibilities for automating human tasks. While prior work has focused on well-defined tasks with specified goals, the c…
ChartCitor: Multi-Agent Framework for Fine-Grained Chart Visual Attribution
Kanika Goswami, Puneet Mathur, Ryan Rossi +1
Large Language Models (LLMs) can perform chart question-answering tasks but often generate unverified hallucinated responses. Existing answer attribution methods struggle to ground…
PlotGen: Multi-Agent LLM-based Scientific Data Visualization via Multimodal Feedback
Kanika Goswami, Puneet Mathur, Ryan Rossi +1
Scientific data visualization is pivotal for transforming raw data into comprehensible visual representations, enabling pattern recognition, forecasting, and the presentation of da…
From Selection to Generation: A Survey of LLM-based Active Learning
Yu Xia, Subhojyoti Mukherjee, Zhouhang Xie +31
Active Learning (AL) has been a powerful paradigm for improving model efficiency and performance by selecting the most informative data points for labeling and training. In recent…
MODS: Moderating a Mixture of Document Speakers to Summarize Debatable Queries in Document Collections
Nishant Balepur, Alexa Siu, Nedim Lipka +4
Query-focused summarization (QFS) gives a summary of documents to answer a query. Past QFS work assumes queries have one answer, ignoring debatable ones (Is law school worth it?).…
PlotEdit: Natural Language-Driven Accessible Chart Editing in PDFs via Multimodal LLM Agents
Kanika Goswami, Puneet Mathur, Ryan Rossi +1
Chart visualizations, while essential for data interpretation and communication, are predominantly accessible only as images in PDFs, lacking source data tables and stylistic infor…