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20242026
most citedSpeculative RAG: Enhancing Retrieval Augmented Generation through Drafting

7 citations · 12 across the 20 of their papers we have counts for

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11 papers · 1 filter

cs.AI2026

Harmony Harness: Multi-Objective Self-Evolution of Agent Harnesses

Weichen Yu, Lesly Miculicich, Bhavana Dalvi Mishra +5

Recent work on self-evolving LLM agents treats the agent harness as an optimization target that can be iteratively improved through execution feedback. Existing approaches, however…

cs.AI2026

VEPA: Verified Evolving Formal Policy for Lifelong LLM Agent Guardrails

Duy Nguyen, Lesly Miculicich, Bhavana Dalvi Mishra +5

LLM agents increasingly operate over sensitive resources, such as private documents and mutable system states, which can create serious safety and security risks. Runtime guardrail…

cs.CR2026

ASPIRE: Agentic Safety & Prompt Injection Red-teaming Engine

Pengfei He, Deep Mitra, Vishesh Sharma +4

LLM agents retrieve untrusted content and act through tools, creating indirect prompt-injection risks that can cause unauthorized actions or persistent state changes. Existing auto…

cs.CR2026

PI-Hunter: Automated Red-Teaming for Exposing and Localizing Prompt Injections

Pengfei He, Lesly Miculicich, Vishesh Sharma +5

Large Language Models (LLMs) are rapidly evolving into agentic systems that interact with external tools and environments, introducing new security risks such as indirect prompt in…

cs.LG2026

LiSA: Lifelong Safety Adaptation via Conservative Policy Induction

Minbeom Kim, Lesly Miculicich, Bhavana Dalvi Mishra +6

As AI agents move from chat interfaces to systems that read private data, call tools, and execute multi-step workflows, guardrails become a last line of defense against concrete de…

cs.CL2026

RubricEM: Meta-RL with Rubric-guided Policy Decomposition beyond Verifiable Rewards

Gaotang Li, Bhavana Dalvi Mishra, Zifeng Wang +9

Deep research agents plan, search, evaluate evidence, and synthesize long-form reports. Training these agents with reinforcement learning (RL) is challenging because they operate o…

cs.CV2026

ARD: Agentic Autoregressive Diffusion for Long Video Consistency

Do Xuan Long, Yale Song, Min-Yen Kan +2

Synthesizing consistent and coherent long video remains a fundamental challenge. Existing methods suffer from semantic drift and narrative collapse over long horizons. We present A…

cs.CL2026

PolicyBank: Evolving Policy Understanding for LLM Agents

Jihye Choi, Jinsung Yoon, Long T. Le +2

LLM agents operating under organizational policies must comply with authorization constraints typically specified in natural language. In practice, such specifications inevitably c…

cs.AI2026

TFRBench: A Reasoning Benchmark for Evaluating Forecasting Systems

Md Atik Ahamed, Mihir Parmar, Palash Goyal +7

We introduce TFRBench, the first benchmark designed to evaluate the reasoning capabilities of forecasting systems. Traditionally, time-series forecasting has been evaluated solely…

cs.CR2026

CausalArmor: Efficient Indirect Prompt Injection Guardrails via Causal Attribution

Minbeom Kim, Mihir Parmar, Phillip Wallis +5

AI agents equipped with tool-calling capabilities are susceptible to Indirect Prompt Injection (IPI) attacks. In this attack scenario, malicious commands hidden within untrusted co…

cs.LG2026

Co-RedTeam: Orchestrated Security Discovery and Exploitation with LLM Agents

Pengfei He, Ash Fox, Lesly Miculicich +7

Large language models (LLMs) have shown promise in assisting cybersecurity tasks, yet existing approaches struggle with automatic vulnerability discovery and exploitation due to li…