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20242026
most citedInjecting Domain-Specific Knowledge into Large Language Models: A Comprehensive Survey

10 citations · 12 across the 16 of their papers we have counts for

collaborators

17 papers

cs.AI2026

RIFAR: Reliability-Informed and Forgetting-Aware Replay for Continual Robot Learning with World-Action Models

Zirui Song, Tu Lin, Zirong Song +11

Genuine embodied agency requires robots to turn continuous real-world experience into lasting, transferable skills. This demands continual learning that integrates new capabilities…

cs.CL2026

Style Wins, Substance Loses: A Diagnosis of LLM-as-Judge in Idea Generation

Fengxian Ji, Yuke Li, Jingpu Yang +8

However, whether these judges truly evaluate the scientific substance of ideas or are influenced by superficial stylistic presentation remains an open question. To address this que…

cs.LG2026

Parametric Memory Decoding for Zero-Shot Routing in LoRA-Based External Parametric Memory

Fengxian Ji, Zhuohan Xie, Jingpu Yang +3

With the rise of parametric memory, LoRA-based External Parametric Memory (EPM) has emerged as a modular solution, but existing routing methods often introduce additional training,…

cs.AI2026

Text-Driven 3D Indoor Scene Synthesis in Non-Manhattan Environments

Xianhui Meng, Zirui Song, Yuchen Zhang +10

Large Language Models (LLMs) have demonstrated remarkable capabilities in 3D indoor synthesis for Manhattan environments. However, existing methods often fail to capture plausible…

cs.CL2026

The Cylindrical Representation Hypothesis for Language Model Steering

Lang Gao, Jinghui Zhang, Wei Liu +7

Steering is a widely used technique for controlling large language models, yet its effects are often unstable and hard to predict. Existing theoretical accounts are largely based o…

cs.LG2026

Distinguishable Deletion: Unifying Knowledge Erasure and Refusal for Large Language Model Unlearning

Puning Yang, Junchi Yu, Qizhou Wang +3

Mitigating sensitive and harmful outputs is fundamental to ensuring safe deployment of LLMs. Existing approaches typically follow two paradigms: Knowledge Deletion (KD), which eras…

cs.CV2026

TextAlign: Preference Alignment for Text Rendering with Hierarchical Rewards

Mingxuan Cui, Jingpu Yang, Fengxian Ji +7

Faithful text rendering remains a persistent weakness of large text-to-image generative models, as it requires both semantic instruction following and fine-grained glyph-level stru…

cs.CV2026

FineState-Bench: Benchmarking State-Conditioned Grounding for Fine-grained GUI State Setting

Fengxian Ji, Jingpu Yang, Zirui Song +5

Despite the rapid progress of large vision-language models (LVLMs), fine-grained, state-conditioned GUI interaction remains challenging. Current evaluations offer limited coverage,…

cs.CV2026

ServImage: An Image Generation and Editing Benchmark from Real-world Commercial Imaging Services

Fengxian Ji, Jingpu Yang, Zirui Song +5

Recent image generation and editing models demonstrate robust adherence to instructions and high visual quality on academic benchmarks. However, their performance on paid, real-wor…

cs.CV2026

FlashSign: Pose-Free Guidance for Efficient Sign Language Video Generation

Liuzhou Zhang, Zeyu Zhang, Biao Wu +10

Sign language plays a crucial role in bridging communication gaps between the deaf and hard-of-hearing communities. However, existing sign language video generation models often re…

cs.CV2025

FineState-Bench: A Comprehensive Benchmark for Fine-Grained State Control in GUI Agents

Fengxian Ji, Jingpu Yang, Zirui Song +6

With the rapid advancement of generative artificial intelligence technology, Graphical User Interface (GUI) agents have demonstrated tremendous potential for autonomously managing…

cs.LG2025

Divide-Fuse-Conquer: Eliciting "Aha Moments" in Multi-Scenario Games

Xiaoqing Zhang, Huabin Zheng, Ang Lv +5

Large language models (LLMs) have been observed to suddenly exhibit advanced reasoning abilities during reinforcement learning (RL), resembling an ``aha moment'' triggered by simpl…

cs.RO2025

ManipLVM-R1: Reinforcement Learning for Reasoning in Embodied Manipulation with Large Vision-Language Models

Zirui Song, Guangxian Ouyang, Mingzhe Li +10

Large Vision-Language Models (LVLMs) have recently advanced robotic manipulation by leveraging vision for scene perception and language for instruction following. However, existing…

cs.CV2025

Geolocation with Real Human Gameplay Data: A Large-Scale Dataset and Human-Like Reasoning Framework

Zirui Song, Jingpu Yang, Yuan Huang +6

Geolocation, the task of identifying an image's location, requires complex reasoning and is crucial for navigation, monitoring, and cultural preservation. However, current methods…

cs.CL2025★ 10 cited

Injecting Domain-Specific Knowledge into Large Language Models: A Comprehensive Survey

Zirui Song, Bin Yan, Yuhan Liu +4

Large Language Models (LLMs) have demonstrated remarkable success in various tasks such as natural language understanding, text summarization, and machine translation. However, the…

cs.RO2024

Hazards in Daily Life? Enabling Robots to Proactively Detect and Resolve Anomalies

Zirui Song, Guangxian Ouyang, Meng Fang +9

Existing household robots have made significant progress in performing routine tasks, such as cleaning floors or delivering objects. However, a key limitation of these robots is th…

cs.AI2024★ 2 cited

MMAC-Copilot: Multi-modal Agent Collaboration Operating Copilot

Zirui Song, Yaohang Li, Meng Fang +6

Large language model agents that interact with PC applications often face limitations due to their singular mode of interaction with real-world environments, leading to restricted…