Papers by Tongxin Li

3 papers
Beyond Numeric Rewards: In-Context Dueling Bandits with LLM Agents (2025.findings-acl)

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Challenge: In-Context Reinforcement Learning (ICRL) is a frontier paradigm for RL problems . authors find that LLMs can generalize cross-domain to perform ICRL on a stateless preference-based RL problem.
Approach: They propose an agentic-flow framework that integrates off-the-shelf DB algorithm support with LLM agents through fine-grained adaptive interplay.
Outcome: The proposed framework can generalize cross-domain to perform ICRL on a stateless preference-based RL problem.
R-Judge: Benchmarking Safety Risk Awareness for LLM Agents (2024.findings-emnlp)

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Challenge: Large language models (LLMs) have shown compelling abilities in reasoning, decision-making, and instruction following.
Approach: They propose a benchmark to evaluate the proficiency of large language models (LLMs) in judging and identifying safety risks given agent interaction records.
Outcome: The proposed model outperforms the best-performing model, GPT-4o, while no other models significantly exceed the random.
TMID: A Comprehensive Real-world Dataset for Trademark Infringement Detection in E-Commerce (2023.emnlp-industry)

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Challenge: Annually, e-commerce platforms incur substantial financial losses due to trademark infringements.
Approach: They propose a dataset to detect trademark infringement in merchant registrations . they use legal rules and contextual information from Alipay to gather contextual information with annotations from legal experts.
Outcome: The proposed dataset is sourced from Alipay, one of the world’s largest e-commerce and digital payment platforms.

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