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Song-Lin Lv

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author3
  • middle author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.AI2
  • cs.LG2

identity via Semantic Scholar / OpenAlex

collaborators

4 papers

cs.AI2026

CoRT: Counterfactual Replay for Token-Level Rubric-Guided Policy Optimization

Bo-Wen Zhang, Junwei He, Wen Wang +5

Rubric-based reinforcement learning enriches language model training by evaluating model outputs against explicit criteria. Yet in GRPO-style pipelines, these structured judgments…

cs.AI2026

Can Agents Generalize to the Open World? Unveiling the Fragility of Static Training in Tool Use

Song-Lin Lv, Weiming Wu, Rui Zhu +2

While Large Language Model (LLM) agents demonstrate proficiency in static benchmarks, their deployment in real-world scenarios is hindered by the dynamic nature of user queries, to…

cs.LG2025

Unlabeled Data vs. Pre-trained Knowledge: Rethinking SSL in the Era of Large Models

Song-Lin Lv, Rui Zhu, Tong Wei +2

Semi-supervised learning (SSL) alleviates the cost of data labeling process by exploiting unlabeled data and has achieved promising results. Meanwhile, with the development of larg…

cs.LG2025

BMIP: Bi-directional Modality Interaction Prompt Learning for VLM

Song-Lin Lv, Yu-Yang Chen, Zhi Zhou +2

Vision-language models (VLMs) have exhibited remarkable generalization capabilities, and prompt learning for VLMs has attracted great attention for the ability to adapt pre-trained…

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