{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/emotion-recognition-in-conversation/papers/2","list_of":"/task/emotion-recognition-in-conversation","task":"Emotion Recognition in Conversation","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":2,"pages_in_order":2,"rows_per_page":100,"rows":[101,141],"of":141,"counts":{"archive_papers_tagged":141,"with_a_code_link":83,"where_syntology_ran_a_sample":15,"not_listed_spam_title":0,"listed":141,"listed_where_code_ran":15,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":12,"every_run_a_failure_of_syntologys_instrument":3,"listed_with_a_run_with_no_instrument_failure":12,"listed_every_run_a_failure_of_syntologys_instrument":3,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/emotion-recognition-in-conversation","prev":"/task/emotion-recognition-in-conversation","next":null,"papers":[{"url":null,"slug":"efficient-cross-task-prompt-tuning-for-few","title":"Efficient Cross-Task Prompt Tuning for Few-Shot Conversational Emotion Recognition","date":"2023-10-23","arxiv_id":"2310.14614","repositories_listed":0,"syntology":null},{"url":"/paper/multimodal-prompt-transformer-with-hybrid","slug":"multimodal-prompt-transformer-with-hybrid","title":"Multimodal Prompt Transformer with Hybrid Contrastive Learning for Emotion Recognition in Conversation","date":"2023-10-04","arxiv_id":"2310.04456","repositories_listed":0,"syntology":null},{"url":null,"slug":"watch-the-speakers-a-hybrid-continuous","title":"Watch the Speakers: A Hybrid Continuous Attribution Network for Emotion Recognition in Conversation With Emotion Disentanglement","date":"2023-09-18","arxiv_id":"2309.09799","repositories_listed":0,"syntology":null},{"url":"/paper/fuzzy-fingerprinting-transformer-language","slug":"fuzzy-fingerprinting-transformer-language","title":"Fuzzy Fingerprinting Transformer Language-Models for Emotion Recognition in Conversations","date":"2023-09-08","arxiv_id":"2309.04292","repositories_listed":0,"syntology":null},{"url":null,"slug":"simple-model-also-works-a-novel-emotion","title":"ERNetCL: A novel emotion recognition network in textual conversation based on curriculum learning strategy","date":"2023-08-12","arxiv_id":"2308.06450","repositories_listed":0,"syntology":null},{"url":"/paper/revisiting-disentanglement-and-fusion-on","slug":"revisiting-disentanglement-and-fusion-on","title":"Revisiting Disentanglement and Fusion on Modality and Context in Conversational Multimodal Emotion Recognition","date":"2023-08-08","arxiv_id":"2308.04502","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-dual-stream-recurrence-attention-network","title":"A Dual-Stream Recurrence-Attention Network With Global-Local Awareness for Emotion Recognition in Textual Dialog","date":"2023-07-02","arxiv_id":"2307.00449","repositories_listed":0,"syntology":null},{"url":null,"slug":"si-lstm-speaker-hybrid-long-short-term-memory","title":"SI-LSTM: Speaker Hybrid Long-short Term Memory and Cross Modal Attention for Emotion Recognition in Conversation","date":"2023-05-04","arxiv_id":"2305.03506","repositories_listed":0,"syntology":null},{"url":"/paper/hcam-hierarchical-cross-attention-model-for","slug":"hcam-hierarchical-cross-attention-model-for","title":"HCAM -- Hierarchical Cross Attention Model for Multi-modal Emotion Recognition","date":"2023-04-14","arxiv_id":"2304.06910","repositories_listed":0,"syntology":null},{"url":null,"slug":"bert-erc-fine-tuning-bert-is-enough-for","title":"BERT-ERC: Fine-tuning BERT is Enough for Emotion Recognition in Conversation","date":"2023-01-17","arxiv_id":"2301.06745","repositories_listed":0,"syntology":null},{"url":"/paper/korean-drama-scene-transcript-dataset-for","slug":"korean-drama-scene-transcript-dataset-for","title":"Korean Drama Scene Transcript Dataset for Emotion Recognition in Conversations","date":"2022-11-11","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"dialogueein-emotion-interaction-network-for","title":"DialogueEIN: Emotion Interaction Network for Dialogue Affective Analysis","date":"2022-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"emotion-recognition-in-conversation-using","title":"Emotion Recognition in Conversation using Probabilistic Soft Logic","date":"2022-07-14","arxiv_id":"2207.07238","repositories_listed":0,"syntology":null},{"url":"/paper/static-and-dynamic-speaker-modeling-based-on","slug":"static-and-dynamic-speaker-modeling-based-on","title":"Static and Dynamic Speaker Modeling based on Graph Neural Network for Emotion Recognition in Conversation","date":"2022-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"speaker-guided-encoder-decoder-framework-for","title":"Speaker-Guided Encoder-Decoder Framework for Emotion Recognition in Conversation","date":"2022-06-07","arxiv_id":"2206.03173","repositories_listed":0,"syntology":null},{"url":"/paper/m2fnet-multi-modal-fusion-network-for-emotion","slug":"m2fnet-multi-modal-fusion-network-for-emotion","title":"M2FNet: Multi-modal Fusion Network for Emotion Recognition in Conversation","date":"2022-06-05","arxiv_id":"2206.02187","repositories_listed":0,"syntology":null},{"url":null,"slug":"mmdag-multimodal-directed-acyclic-graph","title":"MMDAG: Multimodal Directed Acyclic Graph Network for Emotion Recognition in Conversation","date":"2022-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"m2r2-missing-modality-robust-emotion","title":"M2R2: Missing-Modality Robust emotion Recognition framework with iterative data augmentation","date":"2022-05-05","arxiv_id":"2205.02524","repositories_listed":0,"syntology":null},{"url":"/paper/emocaps-emotion-capsule-based-model-for","slug":"emocaps-emotion-capsule-based-model-for","title":"EmoCaps: Emotion Capsule based Model for Conversational Emotion Recognition","date":"2022-03-25","arxiv_id":"2203.13504","repositories_listed":0,"syntology":null},{"url":null,"slug":"emocaps-emotion-capsule-based-model-for-1","title":"EmoCaps:Emotion Capsule based Model for Conversationl Emotion Recognition","date":"2022-03-25","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":"/paper/s-page-a-speaker-and-position-aware-graph","slug":"s-page-a-speaker-and-position-aware-graph","title":"S+PAGE: A Speaker and Position-Aware Graph Neural Network Model for Emotion Recognition in Conversation","date":"2021-12-23","arxiv_id":"2112.12389","repositories_listed":0,"syntology":null},{"url":"/paper/hybrid-curriculum-learning-for-emotion","slug":"hybrid-curriculum-learning-for-emotion","title":"Hybrid Curriculum Learning for Emotion Recognition in Conversation","date":"2021-12-22","arxiv_id":"2112.11718","repositories_listed":0,"syntology":null},{"url":"/paper/a-discourse-aware-graph-neural-network-for","slug":"a-discourse-aware-graph-neural-network-for","title":"A Discourse-Aware Graph Neural Network for Emotion Recognition in Multi-Party Conversation","date":"2021-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":"/paper/knowledge-interactive-network-with-sentiment","slug":"knowledge-interactive-network-with-sentiment","title":"Knowledge-Interactive Network with Sentiment Polarity Intensity-Aware Multi-Task Learning for Emotion Recognition in Conversations","date":"2021-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"compm-context-modeling-with-speaker-s-pre-1","title":"CoMPM: Context Modeling with Speaker's Pre-trained Memory Tracking for Emotion Recognition in Conversation","date":"2021-10-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":"/paper/topic-driven-and-knowledge-aware-transformer","slug":"topic-driven-and-knowledge-aware-transformer","title":"Topic-Driven and Knowledge-Aware Transformer for Dialogue Emotion Detection","date":"2021-06-02","arxiv_id":"2106.01071","repositories_listed":0,"syntology":null},{"url":"/paper/coin-conversational-interactive-networks-for","slug":"coin-conversational-interactive-networks-for","title":"COIN: Conversational Interactive Networks for Emotion Recognition in Conversation","date":"2021-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"emotion-dynamics-modeling-via-bert","title":"Emotion Dynamics Modeling via BERT","date":"2021-04-15","arxiv_id":"2104.07252","repositories_listed":0,"syntology":null},{"url":"/paper/an-iterative-emotion-interaction-network-for","slug":"an-iterative-emotion-interaction-network-for","title":"An Iterative Emotion Interaction Network for Emotion Recognition in Conversations","date":"2020-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":"/paper/hitrans-a-transformer-based-context-and","slug":"hitrans-a-transformer-based-context-and","title":"HiTrans: A Transformer-Based Context- and Speaker-Sensitive Model for Emotion Detection in Conversations","date":"2020-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":"/paper/summarize-before-aggregate-a-global-to-local","slug":"summarize-before-aggregate-a-global-to-local","title":"Summarize before Aggregate: A Global-to-local Heterogeneous Graph Inference Network for Conversational Emotion Recognition","date":"2020-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"dialoguetrm-exploring-the-intra-and-inter","title":"DialogueTRM: Exploring the Intra- and Inter-Modal Emotional Behaviors in the Conversation","date":"2020-10-15","arxiv_id":"2010.07637","repositories_listed":0,"syntology":null},{"url":"/paper/hierarchical-pre-training-for-sequence","slug":"hierarchical-pre-training-for-sequence","title":"Hierarchical Pre-training for Sequence Labelling in Spoken Dialog","date":"2020-09-23","arxiv_id":"2009.11152","repositories_listed":0,"syntology":null},{"url":"/paper/contextualized-emotion-recognition-in","slug":"contextualized-emotion-recognition-in","title":"Contextualized Emotion Recognition in Conversation as Sequence Tagging","date":"2020-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":"/paper/multi-task-learning-network-for-emotion","slug":"multi-task-learning-network-for-emotion","title":"Multi-Task Learning with Auxiliary Speaker Identification for Conversational Emotion Recognition","date":"2020-03-03","arxiv_id":"2003.01478","repositories_listed":0,"syntology":null},{"url":"/paper/hierarchical-transformer-network-for","slug":"hierarchical-transformer-network-for","title":"Hierarchical Transformer Network for Utterance-level Emotion Recognition","date":"2020-02-18","arxiv_id":"2002.07551","repositories_listed":0,"syntology":null},{"url":"/paper/neural-feature-extraction-for-contextual","slug":"neural-feature-extraction-for-contextual","title":"Neural Feature Extraction for Contextual Emotion Detection","date":"2019-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":"/paper/modeling-both-context-and-speaker-sensitive","slug":"modeling-both-context-and-speaker-sensitive","title":"Modeling both context- and speaker-sensitive dependence for emotion detection in multi-speaker conversations","date":"2019-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":"/paper/attention-based-modeling-for-emotion","slug":"attention-based-modeling-for-emotion","title":"Attention-based Modeling for Emotion Detection and Classification in Textual Conversations","date":"2019-06-14","arxiv_id":"1906.07020","repositories_listed":0,"syntology":null},{"url":"/paper/symantoresearch-at-semeval-2019-task-3","slug":"symantoresearch-at-semeval-2019-task-3","title":"SymantoResearch at SemEval-2019 Task 3: Combined Neural Models for Emotion Classification in Human-Chatbot Conversations","date":"2019-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":"/paper/recurrent-neural-network-for-text","slug":"recurrent-neural-network-for-text","title":"Recurrent Neural Network for Text Classification with Multi-Task Learning","date":"2016-05-17","arxiv_id":"1605.05101","repositories_listed":0,"syntology":null}],"record_sha256":"5fe5ff89191a89b6b8ab916a897a8228a548f1d5fa319632573edda78cacdba0","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}