{"list":"other","total":69,"rows":[{"id":"1706.03762","title":"Attention Is All You Need","created":"2017-06-12","cited_by_count":60361},{"id":"1512.03385","title":"Deep Residual Learning for Image Recognition","created":"2015-12-10","cited_by_count":52096},{"id":"1810.04805","title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding","created":"2018-10-11","cited_by_count":40399},{"id":"2103.00020","title":"Learning Transferable Visual Models From Natural Language Supervision","created":"2021-02-26","cited_by_count":33744},{"id":"2010.11929","title":"An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale","created":"2020-10-22","cited_by_count":30186},{"id":"2407.21783","title":"The Llama 3 Herd of Models","created":"2024-07-31","cited_by_count":14715},{"id":"1910.10683","title":"Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer","created":"2019-10-23","cited_by_count":14599},{"id":"1907.11692","title":"RoBERTa: A Robustly Optimized BERT Pretraining Approach","created":"2019-07-26","cited_by_count":13372},{"id":"2304.07193","title":"DINOv2: Learning Robust Visual Features without Supervision","created":"2023-04-14","cited_by_count":7974},{"id":"2009.03300","title":"Measuring Massive Multitask Language Understanding","created":"2020-09-07","cited_by_count":7963},{"id":"2304.08485","title":"Visual Instruction Tuning","created":"2023-04-17","cited_by_count":7869},{"id":"2501.12948","title":"DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning","created":"2025-01-22","cited_by_count":6330},{"id":"1910.13461","title":"BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension","created":"2019-10-29","cited_by_count":5893},{"id":"2312.00752","title":"Mamba: Linear-Time Sequence Modeling with Selective State Spaces","created":"2023-12-01","cited_by_count":4718},{"id":"2201.12086","title":"BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation","created":"2022-01-28","cited_by_count":4322},{"id":"2212.04356","title":"Robust Speech Recognition via Large-Scale Weak Supervision","created":"2022-12-06","cited_by_count":4057},{"id":"2006.11477","title":"wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations","created":"2020-06-20","cited_by_count":3905},{"id":"2205.01068","title":"OPT: Open Pre-trained Transformer Language Models","created":"2022-05-02","cited_by_count":3512},{"id":"1310.4546","title":"Distributed Representations of Words and Phrases and their Compositionality","created":"2013-10-16","cited_by_count":3474},{"id":"2004.05150","title":"Longformer: The Long-Document Transformer","created":"2020-04-10","cited_by_count":3413},{"id":"2210.11416","title":"Scaling Instruction-Finetuned Language Models","created":"2022-10-20","cited_by_count":3024},{"id":"2305.06500","title":"InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning","created":"2023-05-11","cited_by_count":2876},{"id":"2408.03326","title":"LLaVA-OneVision: Easy Visual Task Transfer","created":"2024-08-06","cited_by_count":2719},{"id":"2106.07447","title":"HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units","created":"2021-06-14","cited_by_count":2342},{"id":"2308.12966","title":"Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond","created":"2023-08-24","cited_by_count":2224},{"id":"2006.03654","title":"DeBERTa: Decoding-enhanced BERT with Disentangled Attention","created":"2020-06-05","cited_by_count":2181},{"id":"2304.01373","title":"Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling","created":"2023-04-03","cited_by_count":1786},{"id":"2007.14062","title":"Big Bird: Transformers for Longer Sequences","created":"2020-07-28","cited_by_count":1684},{"id":"2110.13900","title":"WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing","created":"2021-10-26","cited_by_count":1657},{"id":"2103.15691","title":"ViViT: A Video Vision Transformer","created":"2021-03-29","cited_by_count":1620},{"id":"2203.12602","title":"VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training","created":"2022-03-23","cited_by_count":1322},{"id":"2305.05665","title":"ImageBind: One Embedding Space To Bind Them All","created":"2023-05-09","cited_by_count":1175},{"id":"2406.12793","title":"ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools","created":"2024-06-18","cited_by_count":1121},{"id":"2304.14178","title":"mPLUG-Owl: Modularization Empowers Large Language Models with Multimodality","created":"2023-04-27","cited_by_count":1040},{"id":"2309.10305","title":"Baichuan 2: Open Large-scale Language Models","created":"2023-09-19","cited_by_count":670},{"id":"2112.04482","title":"FLAVA: A Foundational Language And Vision Alignment Model","created":"2021-12-08","cited_by_count":649},{"id":"2210.07316","title":"MTEB: Massive Text Embedding Benchmark","created":"2022-10-13","cited_by_count":640},{"id":"2205.14100","title":"GIT: A Generative Image-to-text Transformer for Vision and Language","created":"2022-05-27","cited_by_count":537},{"id":"2306.16527","title":"OBELICS: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents","created":"2023-06-21","cited_by_count":316},{"id":"2502.02013","title":"Layer by Layer: Uncovering Hidden Representations in Language Models","created":"2025-02-04","cited_by_count":311},{"id":"2105.08209","title":"BookSum: A Collection of Datasets for Long-form Narrative Summarization","created":"2021-05-18","cited_by_count":184},{"id":"1905.11833","title":"Interpreting and improving natural-language processing (in machines) with natural language-processing (in the brain)","created":"2019-05-28","cited_by_count":128},{"id":"2401.08541","title":"Scalable Pre-training of Large Autoregressive Image Models","created":"2024-01-16","cited_by_count":115},{"id":"2305.11863","title":"Scaling laws for language encoding models in fMRI","created":"2023-05-19","cited_by_count":68},{"id":"2206.08657","title":"BridgeTower: Building Bridges Between Encoders in Vision-Language Representation Learning","created":"2022-06-17","cited_by_count":56},{"id":"2312.00575","title":"Instruction-tuning Aligns LLMs to the Human Brain","created":"2023-12-01","cited_by_count":40},{"id":"2212.08094","title":"Joint processing of linguistic properties in brains and language models","created":"2022-12-15","cited_by_count":37},{"id":"2301.03198","title":"The Algonauts Project 2023 Challenge: How the Human Brain Makes Sense of Natural Scenes","created":"2023-01-09","cited_by_count":36},{"id":"2305.12248","title":"Brain encoding models based on multimodal transformers can transfer across language and vision","created":"2023-05-20","cited_by_count":32},{"id":"2311.04930","title":"Large language models implicitly learn to straighten neural sentence trajectories to construct a predictive representation of natural language","created":"2023-11-05","cited_by_count":32},{"id":"2212.10898","title":"Training language models to summarize narratives improves brain alignment","created":"2022-12-21","cited_by_count":26},{"id":"2209.14156","title":"TVLT: Textless Vision-Language Transformer","created":"2022-09-28","cited_by_count":22},{"id":"2301.08164","title":"DiME: Maximizing Mutual Information by a Difference of Matrix-Based Entropies","created":"2023-01-19","cited_by_count":21},{"id":"2307.10246","title":"Deep Neural Networks and Brain Alignment: Brain Encoding and Decoding (Survey)","created":"2023-07-17","cited_by_count":21},{"id":"2410.09230","title":"Improving Semantic Understanding in Speech Language Models via Brain-tuning","created":"2024-10-11","cited_by_count":20},{"id":"2311.04664","title":"Speech language models lack important brain-relevant semantics","created":"2023-11-08","cited_by_count":19},{"id":"2212.00596","title":"Language models and brains align due to more than next-word prediction and word-level information","created":"2022-12-01","cited_by_count":14},{"id":"2409.05771","title":"Evidence from fMRI Supports a Two-Phase Abstraction Process in Language Models","created":"2024-09-09","cited_by_count":13},{"id":"2306.05126","title":"Mapping Brains with Language Models: A Survey","created":"2023-06-08","cited_by_count":8},{"id":"2505.20027","title":"Multi-modal brain encoding models for multi-modal stimuli","created":"2025-05-26","cited_by_count":8},{"id":"2401.15681","title":"From Word Embedding to Reading Embedding Using Large Language Model, EEG and Eye-tracking","created":"2024-01-28","cited_by_count":6},{"id":"2505.22563","title":"Do Large Language Models Think Like the Brain? Sentence-Level Evidences from Layer-Wise Embeddings and fMRI","created":"2025-05-28","cited_by_count":6},{"id":"2505.20029","title":"Correlating instruction-tuning (in multimodal models) with vision-language processing (in the brain)","created":"2025-05-26","cited_by_count":4},{"id":"2508.11536","title":"Language models align with brain regions that represent concepts across modalities","created":"2025-08-15","cited_by_count":4},{"id":"2506.03832","title":"Brain-tuned Speech Models Better Reflect Speech Processing Stages in the Brain","created":"2025-06-04","cited_by_count":3},{"id":"2411.15386","title":"Inducing Human-like Biases in Moral Reasoning Language Models","created":"2024-11-23","cited_by_count":2},{"id":"2504.06843","title":"Integrating Cognitive Processing Signals into Language Models: A Review of Advances, Applications and Future Directions","created":"2025-04-09","cited_by_count":2},{"id":"2506.20489","title":"Brains and language models converge on a shared conceptual space across different languages","created":"2025-06-25","cited_by_count":2},{"id":"2505.12196","title":"Vectors from Larger Language Models Predict Human Reading Time and fMRI Data More Poorly when Dimensionality Expansion is Controlled","created":"2025-05-18","cited_by_count":1}],"next_cursor":null}