collaborators

7 papers

cs.AI2026

CaRE Compute-aware Remasking Evaluation Protocol for Masked Diffusion Language Models

Yash Shah, Abhijit Chakraborty, Vivek Gupta

Masked diffusion language models (MDLMs) are advancing rapidly, yet the evaluation standards needed to reliably interpret their progress have not kept pace. Despite MDLMs becoming…

cs.AI2026

Synapse: Federated Tool Routing via Typed Compendium Artifacts

Abhijit Chakraborty, Yash Shah, Vivek Gupta

The unit of collaboration in federated learning determines what guarantees are even expressible. Flat units like weights, prompts, raw examples, carry no type signature on which pr…

cs.SE2026

SWE-InfraBench: Evaluating Language Models on Cloud Infrastructure Code

Natalia Tarasova, Enrique Balp-Straffon, Aleksei Iancheruk +10

Building infrastructure-as-code (IaC) in cloud computing is a critical task, underpinning the reliability, scalability, and security of modern software systems. Despite the remarka…

cs.AI2026

GamED.AI: A Hierarchical Multi-Agent Framework for Automated Educational Game Generation

Shiven Agarwal, Yash Shah, Ashish Raj Shekhar +2

We introduce GamEDAI, a hierarchical multi-agent framework that transforms instructor-provided questions into fully playable, pedagogically grounded educational games validated thr…

cs.AI2026

OSCAR: Orchestrated Self-verification and Cross-path Refinement

Yash Shah, Abhijit Chakraborty, Naresh Kumar Devulapally +2

Diffusion language models (DLMs) expose their denoising trajectories, offering a natural handle for inference-time control; accordingly, an ideal hallucination mitigation framework…

cs.CL2026

DoPE: Decoy Oriented Perturbation Encapsulation Human-Readable, AI-Hostile Documents for Academic Integrity

Ashish Raj Shekhar, Shiven Agarwal, Priyanuj Bordoloi +3

Multimodal Large Language Models (MLLMs) can directly consume exam documents, threatening conventional assessments and academic integrity. We present DoPE (Decoy-Oriented Perturbat…