activity
20242026
most citedA Survey on Mechanistic Interpretability for Multi-Modal Foundation Models

1 citations · 1 across the 12 of their papers we have counts for

collaborators

13 papers

cs.CV2026

Personalized Image Generation with Reasoning and Reflection

Bo Ni, Ngoc N. Tran, Qinwen Ge +10

Personalized image generation has remained narrowly focused on conditional synthesis from curated visual exemplars, rather than capturing who a user is. In practice, however, a use…

cs.CV2026

A Glance Is All You Need: Single-Pass Fine-Grained Image Captioning with SimLoss

Suryaansh Jain, Rahasya Barkur, Vishal G +8

An image may be worth a thousand words, but most captioning models describe it in only a few. Modern vision-language models produce fluent high-level captions, yet routinely miss t…

cs.CV2026

JigShape: Evaluating Visual-Geometric Reasoning in VLMs through Jigsaw Puzzles

Shawn Li, Wei Yang, Jike Zhong +11

Jigsaw puzzle solving requires jointly reasoning about visual content and geometric constraints, yet existing benchmarks use rectangular cuts that create ambiguous ground truth in…

cs.AI2026

GRASP: GRanularity-Aware Search Policy for Agentic RAG

Varun Gandhi, Jaewook Lee, Shantanu Todmal +4

Agentic retrieval-augmented generation (RAG) extends static RAG by allowing language models to iteratively reason, generate search queries, retrieve evidence, and predict answers.…

cs.CL2026

MultAttnAttrib: Training-Free Multimodal Attribution in Long Document Question Answering

Dang Quang Thien Tran, Quang V. Dang, Vinamra Tyagi +7

As grounded QA systems are increasingly deployed in AI assistants, accurately attributing generated answers to evidence is critical for user trust and model safety. While unimodal…

cs.CL2026

Spinning Straw into Gold: Relabeling LLM Agent Trajectories in Hindsight for Successful Demonstrations

Zichao Li, Gang Wu, Zichao Wang +5

Large language model agents operate in partially observable, long-horizon settings where obtaining supervision remains a major bottleneck. We address this by utilizing a source of…

cs.CV2026

InfinityStory: Unlimited Video Generation with World Consistency and Character-Aware Shot Transitions

Mohamed Elmoghany, Liangbing Zhao, Xiaoqian Shen +27

Generating long-form storytelling videos with consistent visual narratives remains a significant challenge in video synthesis. We present a novel framework, dataset, and a model th…

cs.CL2026

Reasoning-Based Personalized Generation for Users with Sparse Data

Bo Ni, Branislav Kveton, Samyadeep Basu +14

Large Language Model (LLM) personalization holds great promise for tailoring responses by leveraging personal context and history. However, real-world users usually possess sparse…

cs.CV2025

SliderEdit: Continuous Image Editing with Fine-Grained Instruction Control

Arman Zarei, Samyadeep Basu, Mobina Pournemat +3

Instruction-based image editing models have recently achieved impressive performance, enabling complex edits to an input image from a multi-instruction prompt. However, these model…

cs.CL2025

Decomposition-Enhanced Training for Post-Hoc Attributions In Language Models

Sriram Balasubramanian, Samyadeep Basu, Koustava Goswami +6

Large language models (LLMs) are increasingly used for long-document question answering, where reliable attribution to sources is critical for trust. Existing post-hoc attribution…

cs.LG2025★ 1 cited

A Survey on Mechanistic Interpretability for Multi-Modal Foundation Models

Zihao Lin, Samyadeep Basu, Mohammad Beigi +18

The rise of foundation models has transformed machine learning research, prompting efforts to uncover their inner workings and develop more efficient and reliable applications for…

cs.CL2025

On Mechanistic Circuits for Extractive Question-Answering

Samyadeep Basu, Vlad Morariu, Zichao Wang +4

Large language models are increasingly used to process documents and facilitate question-answering on them. In our paper, we extract mechanistic circuits for this real-world langua…

cs.CL2024

Persona-SQ: A Personalized Suggested Question Generation Framework For Real-world Documents

Zihao Lin, Zichao Wang, Yuanting Pan +5

Suggested questions (SQs) provide an effective initial interface for users to engage with their documents in AI-powered reading applications. In practical reading sessions, users h…