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Language Modelling

A language model is a model of natural language. Language models are useful for a variety of tasks, including speech recognition, machine translation, natural language generation (generating more human-like text), optical character recognition, route optimization, handwriting recognition, grammar induction, and information retrieval.

Large language models (LLMs), currently their most advanced form, are predominantly based on transformers trained on larger datasets (frequently using words scraped from the public internet). They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.

Source: Wikipedia

Papers

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Showing 4951–5000 of 17610 papers

TitleStatusHype
The Devil is in the Neurons: Interpreting and Mitigating Social Biases in Pre-trained Language ModelsCode1
RoboGolf: Mastering Real-World Minigolf with a Reflective Multi-Modality Vision-Language Model—0
Regularizing Hidden States Enables Learning Generalizable Reward Model for LLMsCode4
Let the Poem Hit the Rhythm: Using a Byte-Based Transformer for Beat-Aligned Poetry GenerationCode0
Precision Empowers, Excess Distracts: Visual Question Answering With Dynamically Infused Knowledge In Language Models—0
Group and Shuffle: Efficient Structured Orthogonal ParametrizationCode0
Rapport-Driven Virtual Agent: Rapport Building Dialogue Strategy for Improving User Experience at First MeetingCode0
CarLLaVA: Vision language models for camera-only closed-loop drivingCode3
3D-RPE: Enhancing Long-Context Modeling Through 3D Rotary Position Encoding—0
Sycophancy to Subterfuge: Investigating Reward-Tampering in Large Language ModelsCode1
OSPC: Detecting Harmful Memes with Large Language Model as a Catalyst—0
A Probability--Quality Trade-off in Aligned Language Models and its Relation to Sampling Adaptors—0
OpenECAD: An Efficient Visual Language Model for Editable 3D-CAD Design—0
UniBridge: A Unified Approach to Cross-Lingual Transfer Learning for Low-Resource LanguagesCode0
Large language model validity via enhanced conformal prediction methodsCode1
LUMA: A Benchmark Dataset for Learning from Uncertain and Multimodal DataCode1
GEB-1.3B: Open Lightweight Large Language Model—0
CLST: Cold-Start Mitigation in Knowledge Tracing by Aligning a Generative Language Model as a Students' Knowledge Tracer—0
Talking Heads: Understanding Inter-layer Communication in Transformer Language Models—0
Newswire: A Large-Scale Structured Database of a Century of Historical NewsCode1
Multi-Modal Retrieval For Large Language Model Based Speech Recognition—0
Decoding the Diversity: A Review of the Indic AI Research Landscape—0
Investigating the translation capabilities of Large Language Models trained on parallel data onlyCode0
LLM Reading Tea Leaves: Automatically Evaluating Topic Models with Large Language ModelsCode0
StreamBench: Towards Benchmarking Continuous Improvement of Language AgentsCode2
Autonomous Multi-Objective Optimization Using Large Language Model—0
Chain-of-Though (CoT) prompting strategies for medical error detection and correction—0
On the Effects of Heterogeneous Data Sources on Speech-to-Text Foundation Models—0
RH-SQL: Refined Schema and Hardness Prompt for Text-to-SQL—0
DubWise: Video-Guided Speech Duration Control in Multimodal LLM-based Text-to-Speech for Dubbing—0
DiscreteSLU: A Large Language Model with Self-Supervised Discrete Speech Units for Spoken Language Understanding—0
ProxyLM: Predicting Language Model Performance on Multilingual Tasks via Proxy ModelsCode0
An Approach to Build Zero-Shot Slot-Filling System for Industry-Grade Conversational Assistants—0
ElicitationGPT: Text Elicitation Mechanisms via Language Models—0
Conceptual Learning via Embedding Approximations for Reinforcing Interpretability and TransparencyCode0
Enhancing Diagnostic Accuracy in Rare and Common Fundus Diseases with a Knowledge-Rich Vision-Language ModelCode2
On Softmax Direct Preference Optimization for RecommendationCode2
Unlearning with Control: Assessing Real-world Utility for Large Language Model Unlearning—0
Transformers meet Neural Algorithmic Reasoners—0
OpenVLA: An Open-Source Vision-Language-Action ModelCode9
Generative AI-based Prompt Evolution Engineering Design Optimization With Vision-Language Model—0
Enhancing Domain Adaptation through Prompt Gradient AlignmentCode1
Explore the Limits of Omni-modal Pretraining at ScaleCode2
Zero-Shot Learning Over Large Output Spaces : Utilizing Indirect Knowledge Extraction from Large Language Models—0
Multimodal Representation Loss Between Timed Text and Audio for Regularized Speech Separation—0
DualVC 3: Leveraging Language Model Generated Pseudo Context for End-to-end Low Latency Streaming Voice Conversion—0
Advancing High Resolution Vision-Language Models in BiomedicineCode1
PolySpeech: Exploring Unified Multitask Speech Models for Competitiveness with Single-task Models—0
Figuratively Speaking: Authorship Attribution via Multi-Task Figurative Language ModelingCode0
Guiding In-Context Learning of LLMs through Quality Estimation for Machine TranslationCode0
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All datasetsWikiText-103Penn Treebank (Word Level)enwik8The PileWikiText-2LAMBADAOne Billion WordText8Penn Treebank (Character Level)Hutter PrizeOpenWebTextSALMon

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Decay RNNValidation perplexity76.67—Unverified
2GRUValidation perplexity53.78—Unverified
3LSTMValidation perplexity52.73—Unverified
4LSTMTest perplexity48.7—Unverified
5Temporal CNNTest perplexity45.2—Unverified
6TCNTest perplexity45.19—Unverified
7GCNN-8Test perplexity44.9—Unverified
8Neural cache model (size = 100)Test perplexity44.8—Unverified
9Neural cache model (size = 2,000)Test perplexity40.8—Unverified
10GPT-2 SmallTest perplexity37.5—Unverified
#ModelMetricClaimedVerifiedStatus
1TCNTest perplexity108.47—Unverified
2Seq-U-NetTest perplexity107.95—Unverified
3GRU (Bai et al., 2018)Test perplexity92.48—Unverified
4R-TransformerTest perplexity84.38—Unverified
5Zaremba et al. (2014) - LSTM (medium)Test perplexity82.7—Unverified
6Gal & Ghahramani (2016) - Variational LSTM (medium)Test perplexity79.7—Unverified
7LSTM (Bai et al., 2018)Test perplexity78.93—Unverified
8Zaremba et al. (2014) - LSTM (large)Test perplexity78.4—Unverified
9Gal & Ghahramani (2016) - Variational LSTM (large)Test perplexity75.2—Unverified
10Inan et al. (2016) - Variational RHNTest perplexity66—Unverified
#ModelMetricClaimedVerifiedStatus
1LSTM (7 layers)Bit per Character (BPC)1.67—Unverified
2HypernetworksBit per Character (BPC)1.34—Unverified
3SHA-LSTM (4 layers, h=1024, no attention head)Bit per Character (BPC)1.33—Unverified
4LN HM-LSTMBit per Character (BPC)1.32—Unverified
5ByteNetBit per Character (BPC)1.31—Unverified
6Recurrent Highway NetworksBit per Character (BPC)1.27—Unverified
7Large FS-LSTM-4Bit per Character (BPC)1.25—Unverified
8Large mLSTMBit per Character (BPC)1.24—Unverified
9AWD-LSTM (3 layers)Bit per Character (BPC)1.23—Unverified
10Cluster-Former (#C=512)Bit per Character (BPC)1.22—Unverified
#ModelMetricClaimedVerifiedStatus
1Smaller Transformer 126M (pre-trained)Test perplexity33—Unverified
2OPT 125MTest perplexity32.26—Unverified
3Larger Transformer 771M (pre-trained)Test perplexity28.1—Unverified
4OPT 1.3BTest perplexity19.55—Unverified
5GPT-Neo 125MTest perplexity17.83—Unverified
6OPT 2.7BTest perplexity17.81—Unverified
7Smaller Transformer 126M (fine-tuned)Test perplexity12—Unverified
8GPT-Neo 1.3BTest perplexity11.46—Unverified
9Transformer 125MTest perplexity10.7—Unverified
10GPT-Neo 2.7BTest perplexity10.44—Unverified