11 papers
Omni2LoRA: Coherence-Preserving Parametric Memory for Efficient Omni Language Models
Puneet Mathur, Manan Suri, Dinesh Manocha
Omnimodal language models (OLMs) enable unified audio-visual understanding, but processing long joint token sequences makes inference computationally prohibitive. While recent toke…
Frames2LoRA: Parametric Video Internalization for Vision-Language Models
Manan Suri, Sarvesh Baskar, Dinesh Manocha
Processing video in vision-language models is expensive: each frame occupies hundreds of tokens, and inference cost scales with every frame and every repeated query. We introduce F…
DIAGRAMS: A Review Framework for Reasoning-Level Attribution in Diagram QA
Anirudh Iyengar Kaniyar Narayana Iyengar, Tampu Ravi Kumar, Manan Suri +4
Diagram question answering (Diagram QA) requires reasoning-level attribution that links each question-answer pair to all visual regions needed to derive the answer, rather than onl…
DRAGON: A Benchmark for Evidence-Grounded Visual Reasoning over Diagrams
Anirudh Iyengar Kaniyar Narayana Iyengar, Tampu Ravi Kumar, Gaurav Najpande +4
Diagram question answering (DQA) requires models to interpret structured visual representations such as charts, maps, infographics, circuit schematics, and scientific diagrams. Rec…
Learning Illumination Control in Diffusion Models
Nishit Anand, Manan Suri, Christopher Metzler +2
Controlling illumination in images is essential for photography and visual content creation. While closed-source models have demonstrated impressive illumination control, open-sour…
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…