Changle Qu

Orcid: 0009-0004-0038-2077

According to our database1, Changle Qu authored at least 13 papers between 2024 and 2026.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Learning to Retrieve from Agent Trajectories.
CoRR, April, 2026

MatchTIR: Fine-Grained Supervision for Tool-Integrated Reasoning via Bipartite Matching.
CoRR, January, 2026

Room Matters: Dynamic Room-level Collaboration Information Modeling for Live Streaming Recommendation.
Proceedings of the ACM Web Conference 2026, 2026

2025
Tool learning with large language models: a survey.
Frontiers Comput. Sci., August, 2025

KuaiLive: A Real-time Interactive Dataset for Live Streaming Recommendation.
CoRR, August, 2025

Towards AI Search Paradigm.
CoRR, June, 2025

Bridging Short Videos and Streamers with Multi-Graph Contrastive Learning for Live Streaming Recommendation.
Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2025

Retrieving Intent-covering Demonstrations for Clarification Generation in Conversational Search Systems.
Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.2, 2025

From Exploration to Mastery: Enabling LLMs to Master Tools via Self-Driven Interactions.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Uplift-RAG: Uplift-Driven Knowledge Preference Alignment for Retrieval-Augmented Generation.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025

2024
COLT: Towards Completeness-Oriented Tool Retrieval for Large Language Models.
CoRR, 2024

ReCODE: Modeling Repeat Consumption with Neural ODE.
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

Towards Completeness-Oriented Tool Retrieval for Large Language Models.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024


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