65 citations · 108 across the 17 of their papers we have counts for
18 papers
Granularity-Adaptive Credit Assignment for Long-Horizon LLM Agent Reinforcement Learning
Taoran Liang, Yang Liu, Shang Luo +10
Long-horizon language-model agents trained with reinforcement learning oftenreceive sparse outcome rewards that do not reveal which decisions along a tra-jectory deserve credit. Ep…
Harness-agnostic detection and immunization of reward hacking in self-evolving language models
Rongxin Yang, Yang Liu, Shang Luo +10
Self-evolving language models improve by proposing candidate updates and keeping whatever raises a visible score. When that score is an imperfect proxy for the capability one actua…
Safety Does Not Compose: Non-Decaying Loop State for Autonomous LLM Agents
Chenhao Wu, Haoxuan Jia, Yang Liu +11
Large language model agents are increasingly deployed as autonomous loops. Starting from one human goal, such a system repeatedly discovers work, plans, executes tool calls, verifi…
Hindsight Memory-PRM: Supervising Memory Management with Auditable Hindsight Credit
Haoxuan Jia, Yang Liu, Yingguang Yang +14
Memory operations of long-horizon LLM agents are hard to supervise: an operation's value is unobservable when it is taken. But they are special -- they leave machine-readable evide…
DiffImaginE: Imagine to Verify Entity Types with Diffusion
Feng Zhang, Feiyu Han, Rongxin Yang +11
Multimodal named entity recognition (MNER) determines whether each candidate span and entity-type hypothesis is supported by joint textual and visual evidence. Existing imagine-and…
SAHG: Sector-Anisotropic Hyperbolic Graph Model for Social Bot Detection
Hanning Lu, Yingguang Yang, Jinwei Su +8
LLM-driven social bots can generate fluent, human-like text, reducing the discriminative advantage of content-based detection alone. However, coordinated campaigns still leave rela…
FinHarness: An Inline Lifecycle Safety Harness for Finance LLM Agents
Haoxuan Jia, Yang Liu, Bin Chong +10
Finance LLM agents must simultaneously block prompt-induced unauthorized actions and approve legitimate multi-step business workflows. However, boundary filters often miss irrevers…
ExTax: Explainable Disinformation Detection via Persuasion, Emotion, and Narrative Role Taxonomies
Shang Luo, Yingguang Yang, Zhenchen Sun +8
The democratization of LLMs has accelerated the generation and circulation of highly fluent disinformation, making traditional syntax-semantic verification increasingly insufficien…
FedRio: Personalized Federated Social Bot Detection via Cooperative Reinforced Contrastive Adversarial Distillation
Yingguang Yang, Hao Liu, Xin Zhang +8
Social bot detection is critical to the stability and security of online social platforms. However, current state-of-the-art bot detection models are largely developed in isolation…
RoBCtrl: Attacking GNN-Based Social Bot Detectors via Reinforced Manipulation of Bots Control Interaction
Yingguang Yang, Xianghua Zeng, Qi Wu +5
Social networks have become a crucial source of real-time information for individuals. The influence of social bots within these platforms has garnered considerable attention from…
Boosting Bot Detection via Heterophily-Aware Representation Learning and Prototype-Guided Cluster Discovery
Buyun He, Xiaorui Jiang, Qi Wu +3
Detecting social media bots is essential for maintaining the security and trustworthiness of social networks. While contemporary graph-based detection methods demonstrate promising…
Certainly Bot Or Not? Trustworthy Social Bot Detection via Robust Multi-Modal Neural Processes
Qi Wu, Yingguang Yang, hao liu +4
Social bot detection is crucial for mitigating misinformation, online manipulation, and coordinated inauthentic behavior. While existing neural network-based detectors perform well…
SeBot: Structural Entropy Guided Multi-View Contrastive Learning for Social Bot Detection
Yingguang Yang, Qi Wu, Buyun He +4
Recent advancements in social bot detection have been driven by the adoption of Graph Neural Networks. The social graph, constructed from social network interactions, contains beni…
BotDGT: Dynamicity-aware Social Bot Detection with Dynamic Graph Transformers
Buyun He, Yingguang Yang, Qi Wu +6
Detecting social bots has evolved into a pivotal yet intricate task, aimed at combating the dissemination of misinformation and preserving the authenticity of online interactions.…
BotSCL: Heterophily-aware Social Bot Detection with Supervised Contrastive Learning
Qi Wu, Yingguang Yang, Buyun He +3
Detecting ever-evolving social bots has become increasingly challenging. Advanced bots tend to interact more with humans as a camouflage to evade detection. While graph-based detec…
FedACK: Federated Adversarial Contrastive Knowledge Distillation for Cross-Lingual and Cross-Model Social Bot Detection
Yingguang Yang, Renyu Yang, Hao Peng +4
Social bot detection is of paramount importance to the resilience and security of online social platforms. The state-of-the-art detection models are siloed and have largely overloo…
RoSGAS: Adaptive Social Bot Detection with Reinforced Self-Supervised GNN Architecture Search
Yingguang Yang, Renyu Yang, Yangyang Li +5
Social bots are referred to as the automated accounts on social networks that make attempts to behave like human. While Graph Neural Networks (GNNs) has been massively applied to t…
Reversible Upper Confidence Bound Algorithm to Generate Diverse Optimized Candidates
Bin Chong, Yingguang Yang, Zi-Le Wang +2
Most algorithms for the multi-armed bandit problem in reinforcement learning aimed to maximize the expected reward, which are thus useful in searching the optimized candidate with…