3 citations · 4 across the 18 of their papers we have counts for
19 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…
CyberForge: Verified Vulnerability Injection at Repository Level for Cybersecurity Agent Training
Amine Lbath, Manan Suri, Aurelien Delaitre +4
Despite recent advances, frontier large language model (LLM) agents remain limited in discovering and patching complex vulnerabilities in real-world software. Generally available a…
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…
Platform architecture determines whether recommendation algorithms can shape information quality on social media
Mohammad Hammas Saeed, David A. Broniatowski, Joseph Simons +3
Social media platforms shape public discourse through two fundamental design choices that naturally co-occur in any field investigation: platform architecture, which defines what t…
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…
CodeScout: Contextual Problem Statement Enhancement for Software Agents
Manan Suri, Xiangci Li, Mehdi Shojaie +5
Current AI-powered code assistance tools often struggle with poorly-defined problem statements that lack sufficient task context and requirements specification. Recent analysis of…
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…
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…
Mitigating Memorization in LLMs using Activation Steering
Manan Suri, Nishit Anand, Amisha Bhaskar
The memorization of training data by Large Language Models (LLMs) poses significant risks, including privacy leaks and the regurgitation of copyrighted content. Activation steering…
VisDoM: Multi-Document QA with Visually Rich Elements Using Multimodal Retrieval-Augmented Generation
Manan Suri, Puneet Mathur, Franck Dernoncourt +3
Understanding information from a collection of multiple documents, particularly those with visually rich elements, is important for document-grounded question answering. This paper…
DocEdit-v2: Document Structure Editing Via Multimodal LLM Grounding
Manan Suri, Puneet Mathur, Franck Dernoncourt +5
Document structure editing involves manipulating localized textual, visual, and layout components in document images based on the user's requests. Past works have shown that multim…
ACLM: A Selective-Denoising based Generative Data Augmentation Approach for Low-Resource Complex NER
Sreyan Ghosh, Utkarsh Tyagi, Manan Suri +3
Complex Named Entity Recognition (NER) is the task of detecting linguistically complex named entities in low-context text. In this paper, we present ACLM Attention-map aware keywor…
The Geometry of Multilingual Language Models: An Equality Lens
Cheril Shah, Yashashree Chandak, Manan Suri
Understanding the representations of different languages in multilingual language models is essential for comprehending their cross-lingual properties, predicting their performance…
WADER at SemEval-2023 Task 9: A Weak-labelling framework for Data augmentation in tExt Regression Tasks
Manan Suri, Aaryak Garg, Divya Chaudhary +2
Intimacy is an essential element of human relationships and language is a crucial means of conveying it. Textual intimacy analysis can reveal social norms in different contexts and…
CoSyn: Detecting Implicit Hate Speech in Online Conversations Using a Context Synergized Hyperbolic Network
Sreyan Ghosh, Manan Suri, Purva Chiniya +3
The tremendous growth of social media users interacting in online conversations has led to significant growth in hate speech, affecting people from various demographics. Most of th…
A novel multimodal dynamic fusion network for disfluency detection in spoken utterances
Sreyan Ghosh, Utkarsh Tyagi, Sonal Kumar +2
Disfluency, though originating from human spoken utterances, is primarily studied as a uni-modal text-based Natural Language Processing (NLP) task. Based on early-fusion and self-a…