3 citations · 4 across the 12 of their papers we have counts for
14 papers
Auditing Escalation Reliability in Healthcare LLM Agents: A Perturbation-Controlled Benchmark of Workflow-State Failures
Zihao Zheng, Junyi Yao, Baichuan Li +1
Trustworthy biomedical AI requires reliable action selection when evidence is missing, stale, conflicting, or late, not only accurate answers on static inputs. We instantiate an ep…
Engineering Reliable Commit Gates for Agentic AI: Cost-Aware Verification Portfolios under Common-Mode Data Failures
Zihao Zheng, Baichuan Li, Junyi Yao +1
Agentic systems commit state-changing actions, but additional verifiers can inherit the same upstream fault. We present VP-CONTROL, a runtime-assurance design and deterministic ben…
Toward Workflow-Aware Benchmarking for Healthcare NLP Agents
Junyi Yao, Baichuan Li, Zihao Zheng +1
Large language model (LLM) agents are increasingly proposed for healthcare tasks such as clinical documentation, evidence retrieval, patient messaging, and care coordination. Yet m…
Reliable Financial Named Entity Recognition Under Domain Shift: Confidence Estimation and Selective Prediction
Zihao Zheng, Baichuan Li, Junyi Yao +1
Financial AI systems often train information extractors on one textual register and deploy them across filings, news, and user-generated content, and standard F1 scores do not indi…
Stale Does Not Mean Unsafe: Guard Precision for Tool-Using LLM Agents under Infrastructure State Races
Zihao Zheng, Jiayu Long, Baichuan Li +1
Tool-using language-model agents increasingly mutate schedulers, data pipelines, object stores, and access-control systems. Between an agent's read and its commit, external state c…
Remember, Verify, or Ask? Evaluating Memory Decisions at Reuse Time
Baichuan Li, Junyi Yao, Zihao Zheng
Persistent memory can personalize an LLM agent, but an incorrect durable update can silently distort future behavior. We study the memory-clarification boundary: whether interactio…
Execution Realism and Reproducibility in LLM-Based Trading Systems: A Systematic Scoping Review and Evidence Audit
Junyi Yao, Zihao Zheng, Baichuan Li +1
Execution realism remains weakly standardized in research on large-language-model-based trading systems, limiting comparison and reproduction across backtests, simulations, and por…
Beyond Helpfulness: A Teaching-over-Solving Diagnostic for Measuring Educational Impact in LLM Tutors
Junyi Yao, Zihao Zheng, Baichuan Li
Large language models are increasingly proposed as educational tutors, yet stronger task-solving ability does not necessarily imply stronger learning support. Motivated by recent c…
MoECa: Aligning Feature Reuse with Expert Decomposition in Diffusion Transformers
Maoliang Li, Haojing Chen, Jiayu Chen +4
Diffusion Transformers with Mixture-of-Experts (DiT-MoE) improve model capacity under sparse activation, but diffusion inference is still bottlenecked by redundant computation acro…
Hy-MT2: A Family of Fast, Efficient and Powerful Multilingual Translation Models in the Wild
Mao Zheng, Zheng Li, Tao Chen +10
Hy-MT2 is a family of fast-thinking multilingual translation models designed for complex real-world scenarios. It includes three model sizes: 1.8B, 7B, and 30B-A3B (MoE), all of wh…
Defense Against Prompt Injection Attack by Leveraging Attack Techniques
Yulin Chen, Haoran Li, Zihao Zheng +3
With the advancement of technology, large language models (LLMs) have achieved remarkable performance across various natural language processing (NLP) tasks, powering LLM-integrate…
BaThe: Defense against the Jailbreak Attack in Multimodal Large Language Models by Treating Harmful Instruction as Backdoor Trigger
Yulin Chen, Haoran Li, Yirui Zhang +3
Multimodal Large Language Models (MLLMs) have showcased impressive performance in a variety of multimodal tasks. On the other hand, the integration of additional image modality may…
KNOWCOMP POKEMON Team at DialAM-2024: A Two-Stage Pipeline for Detecting Relations in Dialogical Argument Mining
Zihao Zheng, Zhaowei Wang, Qing Zong +1
Dialogical Argument Mining(DialAM) is an important branch of Argument Mining(AM). DialAM-2024 is a shared task focusing on dialogical argument mining, which requires us to identify…
Simulate and Eliminate: Revoke Backdoors for Generative Large Language Models
Haoran Li, Yulin Chen, Zihao Zheng +4
With rapid advances, generative large language models (LLMs) dominate various Natural Language Processing (NLP) tasks from understanding to reasoning. Yet, language models' inheren…