Papers by Meiqi Wang

6 papers
Calibration-Aware Policy Optimization for Reasoning LLMs (2026.acl-long)

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Challenge: Existing approaches to model calibration are limited or sacrifice gains in reasoning accuracy.
Approach: They propose a method that improves calibration by 15% while boosting accuracy by 5% . they propose GRPO-style algorithms that misalign uncertainty-agnostic advantage estimation .
Outcome: The proposed approach improves calibration by 15% while achieving comparable to or better than GRPO on multiple mathematical reasoning benchmarks.
MMEKG: Multi-modal Event Knowledge Graph towards Universal Representation across Modalities (2022.acl-demo)

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Challenge: Recent Knowledge Graphs (KGs) store billions of world facts in a directed graph, but expression ability of such entity-centric KGs is limited.
Approach: They propose a large-scale multi-modal event knowledge graph named MMEKG that unifies different modalities of knowledge via events.
Outcome: The proposed system unifies different modalities of knowledge via events, which complement and disambiguate each other.
ERGO: Event Relational Graph Transformer for Document-level Event Causality Identification (2022.coling-1)

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Challenge: Existing methods to identify event-event causal relations in a document are noisy and require heuristic rules or external tools.
Approach: They propose a document-level event-event causality identification framework that uses heuristic rules to design edges between events.
Outcome: The proposed framework outperforms existing state-of-the-art methods on two benchmark datasets.
Navigating the Nuances: A Fine-grained Evaluation of Vision-Language Navigation (2024.findings-emnlp)

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Challenge: a new evaluation framework for vision-language navigation is proposed . current evaluation standards hinge on endpoint success rates and path alignment metrics .
Approach: They propose a semi-automatic method for CFG construction with Large-Language Models . they induct data spanning five principal instruction categories and analyze them .
Outcome: The proposed framework diagnoses current models for the Vision-Language Navigation task at a finer-grained level.
Prompt for Extraction? PAIE: Prompting Argument Interaction for Event Argument Extraction (2022.acl-long)

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Challenge: Using a prompt-based model, we find that event argument extraction is efficient and generalized well to few-shot settings.
Approach: They propose a model PAIE for event argument extraction using prompt tuning for extractive objectives.
Outcome: The proposed model can extract arguments with the same role instead of heuristic threshold tuning.
ManCC: A Task-Anchored Benchmark for Manchu–Classical Chinese Cross-Lingual Modeling (2026.findings-acl)

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Challenge: Mainstream research in natural language processing has focused on high-resource and modern languages.
Approach: They propose a task-anchored benchmark for Manchu–Classical Chinese translation . they use a parallel corpus of 16,627 sentence pairs to evaluate the model .
Outcome: The proposed benchmarks show that linguistic differences influence performance and broader language coverage facilitate low-resource transfer.

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