works on

From the 1 of 29 linked papers with an AI index.

activity
20242026
collaborators

29 papers

cs.CV2026

FOLIO: Focused Semantic Memory for Streaming Video Understanding

Haoyang Fan, Dhruv Parikh, Anvitha Ramachandran +4

The paper introduces FOLIO, a training‑free focused semantic memory system that records detailed information about important entities in a streaming video while compactly storing s…

cs.SE2026

SWE-Milestone: Evaluating AI Agents on Continuous Software Evolution

Gangda Deng, Zhaoling Chen, Zhongming Yu +11

Real-world software must continuously evolve to meet ever-changing and open-ended requirements. AI agents, increasingly deployed as long-running systems, are now entrusted to drive…

cs.CV2026

Vision Non-Causal Trapezoidal Mamba: Eliminating Directional Scanning in Vision SSMs with Second-Order Dynamics

Anvitha Ramachandran, Dhruv Parikh, Haoyang Fan +2

State Space Models (SSMs) have emerged as an alternative to Vision Transformers, yet most vision SSMs inherit directional token scanning from causal sequence modeling. While effect…

cs.LG2026

Accurate and Resource-Efficient Federated Continual Learning

Jebacyril Arockiaraj, Dhruv Parikh, Jayashree Adivarahan +2

Federated continual learning (FCL) must learn from distributed task streams under limited resources, such as communication, computation, memory, and label availability. Existing FC…

cs.LG2026

SACHI: Structured Agent Coordination via Holistic Information Integration in Multi-Agent Reinforcement Learning

Nikunj Gupta, James Zachary Hare, Jesse Milzman +2

Cooperative multi-agent reinforcement learning agents that act on partial local observations face a fundamental information bottleneck: the knowledge needed to select jointly optim…

cs.CV2026

Can Graphs Help Vision SSMs See Better?

Dhruv Parikh, Anvitha Ramachandran, Haoyang Fan +3

Vision state space models inherit the efficiency and long-range modeling ability of Mamba-style selective scans. However, their performance depends critically on the representation…