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20242026
most citedTrustworthiness in Retrieval-Augmented Generation Systems: A Survey

16 citations · 17 across the 5 of their papers we have counts for

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5 papers · 1 filter

cs.AI20261 cited

OmniGAIA: Towards Native Omni-Modal AI Agents

Xiaoxi Li, Wenxiang Jiao, Jiarui Jin +10

Human intelligence naturally intertwines omni-modal perception -- spanning vision, audio, and language -- with complex reasoning and tool usage to interact with the world. However,…

cs.AI2026

Agent-World: Scaling Real-World Environment Synthesis for Evolving General Agent Intelligence

Guanting Dong, Junting Lu, Junjie Huang +17

Large language models are increasingly expected to serve as general-purpose agents that interact with external, stateful tool environments. The Model Context Protocol (MCP) and bro…

cs.AI20261 cited

DeepAgent: A General Reasoning Agent with Scalable Toolsets

Xiaoxi Li, Wenxiang Jiao, Jiarui Jin +8

Large reasoning models have demonstrated strong problem-solving abilities, yet real-world tasks often require external tools and long-horizon interactions. Existing agent framework…

cs.AI2025

HiRA: A Hierarchical Reasoning Framework for Decoupled Planning and Execution in Deep Search

Jiajie Jin, Xiaoxi Li, Guanting Dong +5

Complex information needs in real-world search scenarios demand deep reasoning and knowledge synthesis across diverse sources, which traditional retrieval-augmented generation (RAG…

cs.AI2025

Search-o1: Agentic Search-Enhanced Large Reasoning Models

Xiaoxi Li, Guanting Dong, Jiajie Jin +5

Large reasoning models (LRMs) like OpenAI-o1 have demonstrated impressive long stepwise reasoning capabilities through large-scale reinforcement learning. However, their extended r…