Papers by Min Zijun

2 papers
Towards Better Document-level Relation Extraction via Iterative Inference (2022.emnlp-main)

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Challenge: Existing methods only consider feature information of entity pairs, but our model exploits both feature information and previous predictions of entity pair.
Approach: They propose a document-level relation extraction model with iterative inference to extract relations between entities from raw texts.
Outcome: The proposed model outperforms existing methods on three commonly-used datasets.
Orchestrating Tokens and Sequences: Dynamic Hybrid Policy Optimization for RLVR (2026.findings-acl)

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Challenge: Existing RLVR algorithms focus on different granularities and have complementary strengths and limitations.
Approach: They propose a framework for reinforcement learning with verifiable rewards that bridges RLVR and GSPO . group-level importance ratios are used to update a policy, which preserves fine-grained credit assignment .
Outcome: The proposed framework outperforms existing methods on seven reasoning benchmarks.

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