activity
20242026
most citedSafeWorld: Geo-Diverse Safety Alignment

1 citations · 3 across the 16 of their papers we have counts for

collaborators

16 papers

cs.CL2026

Belief Cascades Drive Persuasion in LLM Agent Networks

Haoyi Qiu, Genglin Liu, Pranav Narayanan Venkit +4

Multi-agent LLM systems increasingly debate answers, coordinate research, simulate users, and mediate information flows, making agent-to-agent persuasion a basic but undermeasured…

cs.AI2026

GTA: Generating Long-Horizon Tasks for Web Agents at Scale

Tenghao Huang, Kung-Hsiang Huang, Prafulla Kumar Choubey +4

Web agents, which couple language models with browsing and tool-use capabilities, show promise as open web assistants. Yet progress is increasingly limited by the lack of scalable,…

cs.CL2026

Dont Stop Early: Scalable Enterprise Deep Research with Controlled Information Flow and Evidence-Aware Termination

Prafulla Kumar Choubey, Kung-Hsiang Huang, Pranav Narayanan Venkit +5

Enterprise deep research often fails to produce decision-ready reports due to uneven information coverage, context explosion, and premature stopping. We propose a scalable Enterpri…

cs.AI2026

Agentic Uncertainty Quantification

Jiaxin Zhang, Prafulla Kumar Choubey, Kung-Hsiang Huang +2

Although AI agents have demonstrated impressive capabilities in long-horizon reasoning, their reliability is severely hampered by the ``Spiral of Hallucination,'' where early epist…

cs.CL2025

MMGR: Multi-Modal Generative Reasoning Benchmark and Evaluation

Zefan Cai, Haoyi Qiu, Tianyi Ma +13

Modern multimodal generative models can synthesize visually compelling images and videos, but it remains unclear whether this visual fluency reflects genuine reasoning: when prompt…

cs.CL2025

Seeing is Believing? Evaluating Vision-Language Model Susceptibility in Agent-to-Agent Multimodal Persuasion

Haoyi Qiu, Yilun Zhou, Pranav Narayanan Venkit +4

As autonomous agents increasingly interact, they inevitably attempt to influence one another. While prior work in text-only settings has explored the dynamics of Agent-to-Agent (A2…

cs.CL2025

GUI-KV: Efficient GUI Agents via KV Cache with Spatio-Temporal Awareness

Kung-Hsiang Huang, Haoyi Qiu, Yutong Dai +2

Graphical user interface (GUI) agents built on vision-language models have emerged as a promising approach to automate human-computer workflows. However, they also face the ineffic…

cs.CL2025★ 1 cited

DeepTRACE: Auditing Deep Research AI Systems for Tracking Reliability Across Citations and Evidence

Pranav Narayanan Venkit, Philippe Laban, Yilun Zhou +3

Generative search engines and deep research LLM agents promise trustworthy, source-grounded synthesis, yet users regularly encounter overconfidence, weak sourcing, and confusing ci…

cs.LG2025

Nudging the Boundaries of LLM Reasoning

Justin Chih-Yao Chen, Becky Xiangyu Peng, Prafulla Kumar Choubey +4

Current online reinforcement learning (RL) algorithms like GRPO share a key limitation in LLM reasoning: they cannot learn from problems that are "unsolvable" to the model. In othe…

cs.CL2025

Benchmarking Deep Search over Heterogeneous Enterprise Data

Prafulla Kumar Choubey, Xiangyu Peng, Shilpa Bhagavath +3

We present a new benchmark for evaluating Deep Search--a realistic and complex form of retrieval-augmented generation (RAG) that requires source-aware, multi-hop reasoning over div…

cs.CL2025

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback

Thai Hoang, Kung-Hsiang Huang, Shirley Kokane +12

Large Action Models (LAMs) for AI Agents offer incredible potential but face challenges due to the need for high-quality training data, especially for multi-steps tasks that involv…

cs.CL2025★ 1 cited

CRMArena-Pro: Holistic Assessment of LLM Agents Across Diverse Business Scenarios and Interactions

Kung-Hsiang Huang, Akshara Prabhakar, Onkar Thorat +6

While AI agents hold transformative potential in business, effective performance benchmarking is hindered by the scarcity of public, realistic business data on widely used platform…

cs.CL2025

Multimodal Cultural Safety: Evaluation Framework and Alignment Strategies

Haoyi Qiu, Kung-Hsiang Huang, Ruichen Zheng +2

Large vision-language models (LVLMs) are increasingly deployed in globally distributed applications, such as tourism assistants, yet their ability to produce culturally appropriate…

cs.CL2024★ 1 cited

SafeWorld: Geo-Diverse Safety Alignment

Da Yin, Haoyi Qiu, Kung-Hsiang Huang +2

In the rapidly evolving field of Large Language Models (LLMs), ensuring safety is a crucial and widely discussed topic. However, existing works often overlook the geo-diversity of…

cs.CL2024

CRMArena: Understanding the Capacity of LLM Agents to Perform Professional CRM Tasks in Realistic Environments

Kung-Hsiang Huang, Akshara Prabhakar, Sidharth Dhawan +6

Customer Relationship Management (CRM) systems are vital for modern enterprises, providing a foundation for managing customer interactions and data. Integrating AI agents into CRM…

cs.CL2024

Evaluating Cultural and Social Awareness of LLM Web Agents

Haoyi Qiu, Alexander R. Fabbri, Divyansh Agarwal +4

As large language models (LLMs) expand into performing as agents for real-world applications beyond traditional NLP tasks, evaluating their robustness becomes increasingly importan…