activity
20232026
most citedLitLLMs, LLMs for Literature Review: Are we there yet?

5 citations · 8 across the 14 of their papers we have counts for

collaborators

17 papers

cs.LG2026

KV-streams for Efficient Compaction in Agentic Reinforcement Learning

Emiliano Penaloza, Dane Malenfant, Dheeraj Vattikonda +15

Scaling the horizon of agentic LLMs is bottlenecked by the need to fit ever longer context traces in GPU memory. Context compaction has been the most popular mechanism to alleviate…

cs.CR2026

Backdoor Decontamination Dynamics in LLM Agents

Gabriel Huang, Abhay Puri, Léo Boisvert +4

Open-weight LLM agents are vulnerable to backdoors installed during fine-tuning, which may be undetectable if the trigger conditions are never met during testing. Assuming defender…

cs.CL2026

PrivacyAlign: Contextual Privacy Alignment for LLM Agents

Manveer Singh Tamber, Abhay Puri, Marc-Etienne Brunet +3

AI agents acting on behalf of users are constantly making decisions, and for users to trust their agents, those decisions must align with what they actually want. Privacy is an imp…

cs.GR2026

VectorGym: A Multi-Task Benchmark for SVG Code Generation, Sketching and Editing

Joan Rodriguez, Haotian Zhang, Abhay Puri +14

We introduce VectorGym, a comprehensive benchmark suite for Scalable Vector Graphics (SVG) that spans generation from text and sketches, complex editing, and visual understanding.…

cs.LG2026

Scale Dependent Data Duplication

Joshua Kazdan, Noam Levi, Rylan Schaeffer +6

Data duplication during pretraining can degrade generalization and lead to memorization, motivating aggressive deduplication pipelines. However, at web scale, it is unclear what co…

cs.LG2026

Quantifying the Effect of Test Set Contamination on Generative Evaluations

Rylan Schaeffer, Joshua Kazdan, Baber Abbasi +8

As frontier AI systems are pretrained on web-scale data, test set contamination has become a critical concern for accurately assessing their capabilities. While research has thorou…

cs.CR2025

Indirect Prompt Injections: Are Firewalls All You Need, or Stronger Benchmarks?

Rishika Bhagwatkar, Kevin Kasa, Abhay Puri +5

AI agents are vulnerable to indirect prompt injection attacks, where malicious instructions embedded in external content or tool outputs cause unintended or harmful behavior. Inspi…

cs.CR2025

Malice in Agentland: Down the Rabbit Hole of Backdoors in the AI Supply Chain

Léo Boisvert, Abhay Puri, Chandra Kiran Reddy Evuru +7

While finetuning AI agents on interaction data -- such as web browsing or tool use -- improves their capabilities, it also introduces critical security vulnerabilities within the a…

cs.CL2025

BigCharts-R1: Enhanced Chart Reasoning with Visual Reinforcement Finetuning

Ahmed Masry, Abhay Puri, Masoud Hashemi +13

Charts are essential to data analysis, transforming raw data into clear visual representations that support human decision-making. Although current vision-language models (VLMs) ha…

cs.CV2025

Rendering-Aware Reinforcement Learning for Vector Graphics Generation

Juan A. Rodriguez, Haotian Zhang, Abhay Puri +12

Scalable Vector Graphics (SVG) offer a powerful format for representing visual designs as interpretable code. Recent advances in vision-language models (VLMs) have enabled high-qua…

cs.CR2025

DoomArena: A framework for Testing AI Agents Against Evolving Security Threats

Leo Boisvert, Mihir Bansal, Chandra Kiran Reddy Evuru +9

We present DoomArena, a security evaluation framework for AI agents. DoomArena is designed on three principles: 1) It is a plug-in framework and integrates easily into realistic ag…

cs.CR2025

No, of Course I Can! Deeper Fine-Tuning Attacks That Bypass Token-Level Safety Mechanisms

Joshua Kazdan, Abhay Puri, Rylan Schaeffer +5

Leading language model (LM) providers like OpenAI and Anthropic allow customers to fine-tune frontier LMs for specific use cases. To prevent abuse, these providers apply filters to…

cs.CL2025★ 1 cited

AlignVLM: Bridging Vision and Language Latent Spaces for Multimodal Document Understanding

Ahmed Masry, Juan A. Rodriguez, Tianyu Zhang +19

Aligning visual features with language embeddings is a key challenge in vision-language models (VLMs). The performance of such models hinges on having a good connector that maps vi…

cs.CL2024★ 5 cited

LitLLMs, LLMs for Literature Review: Are we there yet?

Shubham Agarwal, Gaurav Sahu, Abhay Puri +5

Literature reviews are an essential component of scientific research, but they remain time-intensive and challenging to write, especially due to the recent influx of research paper…

cs.LG2024★ 1 cited

BigDocs: An Open Dataset for Training Multimodal Models on Document and Code Tasks

Juan Rodriguez, Xiangru Jian, Siba Smarak Panigrahi +40

Multimodal AI has the potential to significantly enhance document-understanding tasks, such as processing receipts, understanding workflows, extracting data from documents, and sum…

cs.AI2024

InsightBench: Evaluating Business Analytics Agents Through Multi-Step Insight Generation

Gaurav Sahu, Abhay Puri, Juan Rodriguez +11

Data analytics is essential for extracting valuable insights from data that can assist organizations in making effective decisions. We introduce InsightBench, a benchmark dataset w…

cs.CV2023★ 1 cited

StarVector: Generating Scalable Vector Graphics Code from Images and Text

Juan A. Rodriguez, Abhay Puri, Shubham Agarwal +6

Scalable Vector Graphics (SVGs) are vital for modern image rendering due to their scalability and versatility. Previous SVG generation methods have focused on curve-based vectoriza…