Papers by Hongfei Zhang
Multi-pass Decoding for Grammatical Error Correction (2024.emnlp-main)
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| Challenge: | Seq2edit models decode only once without aware of subsequent tokens. |
| Approach: | They propose to iteratively refine the correction results of seq2seq models via Multi-Pass Decoding (MPD) to improve performance, but MPD increases inference costs . they propose to merge the source input and previous round correction result into one sequence. |
| Outcome: | Experiments on the CoNLL-14 and BEA-19 test set show that the proposed approach improves over baselines. |
ParaSuite: Boosting LLM Reasoning via Paradox Resolution (2026.acl-long)
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| Challenge: | Existing benchmarks for paradox research focus on checking basic logical consistency and not reflective reasoning. |
| Approach: | They propose a pipeline dedicated to paradox research that automates data synthesis, evaluation, and training. |
| Outcome: | The proposed pipeline improves paradoxical and general STEM reasoning. |
MultiCMET: A Novel Chinese Benchmark for Understanding Multimodal Metaphor (2023.findings-emnlp)
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| Challenge: | Existing research on multimodal metaphors does not address categorizing the source and target domains in metaphors beyond the English language. |
| Approach: | They propose a Cascading Domain Knowledge Integration benchmark to detect metaphors by introducing domain-specific lexical features. |
| Outcome: | The proposed dataset includes 13,820 text-image pairs of advertisements with manual annotations of the occurrence of metaphors, domain categories, and sentiments metaphors convey. |
AffectCodec: Emotion-Preserving Neural Speech Codec for Expressive Speech Modeling (2026.findings-acl)
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| Challenge: | Existing codecs optimize acoustic reconstruction, leaving emotion expressiveness insufficiently modeled at the representation level. |
| Approach: | They propose an emotion-guided neural speech codec that preserves emotional information while maintaining semantic fidelity and prosodic naturalness. |
| Outcome: | The proposed codec preserves emotional cues while maintaining semantic fidelity and prosodic naturalness. |
Large-Scale Diverse Synthesis for Mid-Training (2026.findings-acl)
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| Challenge: | Existing data synthesis methods generate simplistic and homogeneous QA pairs with limited scale and diversity. |
| Approach: | They propose a framework to synthesize large-scale, diverse, and high-quality QA data for mid-training. |
| Outcome: | The proposed framework improves on 500B-token BoostQA data over pre-training benchmarks. |
Lipschitz Constrained Parameter Initialization for Deep Transformers (2020.acl-main)
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| Challenge: | Existing studies show that deep Transformers have difficulty in training even with residual connection and layer normalization. |
| Approach: | They propose a method that leverages the Lipschitz constraint on the initialization of Transformer parameters to ease the optimization difficulties caused by its multi-layer encoder/decoder structure. |
| Outcome: | The proposed model outperforms previous RNN/CNN models but fails to converge with the original computation order. |
LinkQA: Synthesizing Diverse QA from Multiple Seeds Strongly Linked by Knowledge Points (2026.acl-long)
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| Challenge: | Existing training data is limited in high-quality training data, limiting the ability to produce high-performance LLMs. |
| Approach: | They propose a KP-graph-based synthesis framework that extracts KPs from QA seed data and constructs a graph of KP data from multiple seeds strongly linked by KP. |
| Outcome: | The proposed framework enables flexible control over discipline and difficulty distributions while balancing KP coverage and popularity. |
Learning Source Phrase Representations for Neural Machine Translation (2020.acl-main)
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| Challenge: | Existing approaches to machine translation have been shown to be effective for long sentences . however, the attentional network can't capture long-distance dependencies . |
| Approach: | They propose a multi-head attention mechanism which generates phrase representations from token representations and incorporates them into the Transformer translation model to enhance its ability to capture long-distance relationships. |
| Outcome: | The proposed model can be computed in parallel and improves on the WMT 14 tasks. |
AIPO: Adaptive Information Guided Token-Level Reinforcement Learning for Large Language Model Reasoning (2026.acl-long)
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| Challenge: | Existing RLVR methods focus on all generated tokens rather than on which tokens contribute to reasoning. |
| Approach: | They propose to use a Random–Fourier approximation of the Hilbert–Schmidt Independence Criterion to focus updates on decisive tokens discovered on the fly to improve the efficiency of mutual-information estimation. |
| Outcome: | The proposed approach yields +20% accuracy over strong RLVR baselines while updating merely 10% of tokens, demonstrating superior efficiency and effectiveness. |
Telling the Whole Story: A Manually Annotated Chinese Dataset for the Analysis of Humor in Jokes (D19-1)
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| Challenge: | Humor plays important role in human communication, which makes it important problem for natural language processing. |
| Approach: | They propose a novel annotation scheme to give scenarios of how humor arises in text . they report reasonable agreement between annotators and analyze the dataset . |
| Outcome: | The proposed scheme gives scenarios of how humor arises in text . it contains key words that trigger humor, character relationship, scene, and humor categories . |
CogEvolve: A Multimodal Benchmark for Evaluating Relational Reasoning in Semantic Extension (2026.acl-long)
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| Challenge: | a gap exists between human embodied logic and machine statistical learning . authors: models internalize statistical patterns or mimic static recognition . |
| Approach: | They propose a cognitive linguistic benchmark to test whether large language models internalize statistical logic or not . they find that models function as "Super-Associators" expert at static recognition yet fail at causal reasoning . |
| Outcome: | The proposed model fails at causal reasoning and has a high-fidelity concept representation but lacks transformational operators essential for true relational understanding. |
RealMedDial: A Real Telemedical Dialogue Dataset Collected from Online Chinese Short-Video Clips (2022.coling-1)
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| Challenge: | Existing medical dialogue systems are limited by the lack of corpora and data from real scenarios. |
| Approach: | They construct a Chinese medical dialogue dataset based on real medical consultations. |
| Outcome: | The proposed dataset is applicable to a wide range of NLP tasks with respect to medical dialogue. |
LLM-Driven Implicit Target Augmentation and Fine-Grained Contextual Modeling for Zero-Shot and Few-Shot Stance Detection (2025.emnlp-main)
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| Challenge: | Recent studies on zero-shot and few-shot stance detection neglect implicit yet semantically important targets. |
| Approach: | They propose a framework that uses Large Language Models to annotate implicit targets . they also propose 'DyMCA' to dynamically adjust text-target contributions based on context . |
| Outcome: | The proposed framework achieves state-of-the-art on a benchmark dataset. |
MultiMET: A Multimodal Dataset for Metaphor Understanding (2021.acl-long)
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| Challenge: | Metaphor is a linguistic phenomenon and a cognitive phenomenon structuring human thought, authors say . previous studies focused on texts, partly due to the unavailability of ground truth labels of multimodal metaphor . |
| Approach: | They propose a multimodal metaphor dataset that integrates multimodal text and image . it contains 10,437 text-image pairs with multimodal annotations of occurrences . |
| Outcome: | The proposed dataset examines multimodal cues and their interplay. |
Construction of a Chinese Corpus for the Analysis of the Emotionality of Metaphorical Expressions (P18-2)
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| Challenge: | a corpus of 5,605 manually annotated sentences in Chinese is described . emotion is an abstract and vague conception, which is often described by metaphor . |
| Approach: | They propose to construct a corpus of metaphors annotated with emotion in Chinese . they use an annotation scheme to include linguistic metaphors, emotional categories and intensity . |
| Outcome: | The proposed corpus contains 5,605 manually annotated sentences in Chinese . the authors show that the corpus is large enough to analyze emotions . |
E2E-GMNER: End-to-End Generative Grounded Multimodal Named Entity Recognition (2026.findings-acl)
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| Challenge: | Existing approaches decouple textual entity recognition and visual grounding, leading to error accumulation and suboptimal joint optimization. |
| Approach: | They propose a fully end-to-end generative framework that unifies recognition, semantic typing, visual grounding and implicit knowledge reasoning within a single multimodal large language model. |
| Outcome: | The proposed framework achieves highly competitive performance compared with state-of-the-art methods. |
Mechanistic Insights into Deferred Semantic Drift in LLMs (2026.findings-acl)
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| Challenge: | Large Language Models (LLMs) face a fundamental challenge with delayed disambiguation: how can a model update the meaning of an early, ambiguous token when clarifying context only appears later in the sequence? |
| Approach: | They propose a method to defer semantic re-evaluation to subsequent tokens in a process they call "Deferred Semantic Drift" they demonstrate this mechanism in metaphor comprehension and provide causal validation by steering model outputs towards literal or metaphorical meanings via targeted activation interventions. |
| Outcome: | The proposed model can update the meaning of an ambiguous word when clarifying context arrives only after it has been processed. |
Cultural Bias Matters: A Cross-Cultural Benchmark Dataset and Sentiment-Enriched Model for Understanding Multimodal Metaphors (2025.acl-long)
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| Challenge: | Metaphors are pervasive in communication, making them crucial for natural language processing. |
| Approach: | They propose a multicultural multimodal metaphor dataset designed for cross-cultural studies of metaphor in Chinese and English. |
| Outcome: | The proposed model improves metaphor comprehension across cultural backgrounds and cultural domains. |
Commonality and Individuality! Integrating Humor Commonality with Speaker Individuality for Humor Recognition (2025.naacl-long)
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| Challenge: | Current methods for humor recognition focus on one aspect of humor commonalities, ignoring the multifaceted nature of humor. |
| Approach: | They propose a commonality and individuality incorporated network for humor recognition that integrates multifaceted humor commonalities with speaker individuality. |
| Outcome: | The proposed model integrates multifaceted humor commonalities with speaker individuality to deepen the understanding of humor expressions. |
Multi-Head Highly Parallelized LSTM Decoder for Neural Machine Translation (2021.acl-long)
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| Challenge: | a self-attention network can be easily parallelized at sequence level, but LSTMs are slower to train . a recent study shows that LS models require a lot of computations to perform . |
| Approach: | They propose to compute LSTMs at sequence level to enable sequence-level parallelization . they use a bag-of-words representation of the preceding tokens context to approximate LStms . |
| Outcome: | The proposed model performs better than existing models while being faster to train . the model can be trained efficiently due to the highly parallelized self-attention network . |
Contrastive Attention Mechanism for Abstractive Sentence Summarization (D19-1)
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| Challenge: | Existing attention mechanisms for abstractive sentence summarization are based on rule-based methods and large-scale training corpora. |
| Approach: | They propose a contrastive attention mechanism that extends the sequence-to-sequence framework for abstractive sentence summarization task. |
| Outcome: | The proposed mechanism improves the state-of-the-art on the abstractive sentence summarization task. |
WenetSpeech-Wu: Datasets, Benchmarks, and Models for a Unified Chinese Wu Dialect Speech Processing Ecosystem (2026.findings-acl)
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Chengyou Wang, Mingchen Shao, Jingbin Hu, Zeyu Zhu, Hongfei Xue, Bingshen Mu, Xin Xu, Xingyi Duan, Binbin Zhang, Zhu Pengcheng, Chuang Ding, Xiaojun Zhang, Hui Bu, Lei Xie
| Challenge: | despite its linguistic significance, the Wu dialect of Chinese has long been hindered by the lack of large-scale speech data, standardized evaluation benchmarks, and publicly available models. |
| Approach: | They propose to use WenetSpeech-Wu as a large-scale, multi-dimensionally annotated open-source speech corpus for the Wu dialect of Chinese. |
| Outcome: | The proposed dataset includes 8,000 hours of speech data and strong open-source models . the proposed dataset is competitive and empirically validated . |
Take Its Essence, Discard Its Dross! Debiasing for Toxic Language Detection via Counterfactual Causal Effect (2024.lrec-main)
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| Challenge: | Existing methods to mitigate lexical bias in toxic language detection (TLD) do not exploit the “useful” and “misleading” impact of the bias. |
| Approach: | They propose a counterfactual Causal Debiasing Framework to mitigate lexical bias in toxic language detection (TLD) it preserves the “useful impact” of lexical bias and eliminates the "misleading impact" they propose to use the same framework to analyze the causal effect of a sentence and bias tokens . |
| Outcome: | The proposed framework preserves the “useful impact” of lexical bias and eliminates the ‘misleading impact’ Empirical evaluations show that the proposed model outperforms current debiased models for out-of-distribution data. |
Label-Enhanced Hierarchical Contextualized Representation for Sequential Metaphor Identification (2021.emnlp-main)
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| Challenge: | Recent approaches to identify metaphors ignore extra information from data, such as contextual information and broader discourse information. |
| Approach: | They propose a model augmented with hierarchical contextualized representation to extract more information from both sentence-level and discourse-level. |
| Outcome: | The proposed model outperforms state-of-the-art methods on two tasks using a VUA dataset. |
WildFeedback: Aligning LLMs With In-situ User Interactions And Feedback (2026.acl-long)
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Taiwei Shi, Zhuoer Wang, Longqi Yang, Ying-Chun Lin, Zexue He, Mengting Wan, Pei Zhou, Sujay Kumar Jauhar, Sihao Chen, Shan Xia, Hongfei Zhang, Jieyu Zhao, Xiaofeng Xu, Xia Song, Jennifer Neville
| Challenge: | Traditional alignment methods rely on human annotations and are subjective and misalignment with real-world user preferences. |
| Approach: | They propose a framework that leverages in-situ user feedback during conversations with LLMs to create preference datasets automatically. |
| Outcome: | The proposed framework identifies and classifies user feedback to LLM responses between conversation turns and creates examples of preferred and dispreferred responses according to user preferences. |
Facilitating Fine-grained Detection of Chinese Toxic Language: Hierarchical Taxonomy, Resources, and Benchmarks (2023.acl-long)
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| Challenge: | Existing datasets suffer from a lack of fine-grained annotations, such as the toxic type and expressions with indirect toxicity. |
| Approach: | They propose a benchmark model to detect toxic language by incorporating lexical features into a Chinese dataset to facilitate fine-grained annotations. |
| Outcome: | The proposed model is based on insulting vocabulary containing implicit profanity and is able to detect toxic language with lexical features. |
WECA: A WordNet-Encoded Collocation-Attention Network for Homographic Pun Recognition (D18-1)
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Yufeng Diao, Hongfei Lin, Di Wu, Liang Yang, Kan Xu, Zhihao Yang, Jian Wang, Shaowu Zhang, Bo Xu, Dongyu Zhang
| Challenge: | Homographic puns have a long history in human writing, widely used in written and spoken literature, which intended as jokes. |
| Approach: | They propose a WordNet-encoded model to settle polysemy of homographic puns and a word weighted model for recognizing them. |
| Outcome: | The proposed model can distinguish between homographic pun and non-homographic pun texts. |