SOTAVerified

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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 8601–8650 of 17610 papers

TitleStatusHype
Tuning Large language model for End-to-end Speech Translation—0
LoFT: Local Proxy Fine-tuning For Improving Transferability Of Adversarial Attacks Against Large Language Model—0
What's the Magic Word? A Control Theory of LLM PromptingCode1
PolySketchFormer: Fast Transformers via Sketching Polynomial Kernels—0
Fool Your (Vision and) Language Model With Embarrassingly Simple PermutationsCode1
Improving Emotional Expression and Cohesion in Image-Based Playlist Description and Music Topics: A Continuous Parameterization Approach—0
Controlling Vision-Language Models for Multi-Task Image RestorationCode2
DriveGPT4: Interpretable End-to-end Autonomous Driving via Large Language Model—0
Error Norm Truncation: Robust Training in the Presence of Data Noise for Text Generation Models—0
CAT-LM: Training Language Models on Aligned Code And TestsCode1
Making Retrieval-Augmented Language Models Robust to Irrelevant ContextCode1
Language Model Decoding as Direct Metrics Optimization—0
L2MAC: Large Language Model Automatic Computer for Extensive Code GenerationCode1
Towards LogiGLUE: A Brief Survey and A Benchmark for Analyzing Logical Reasoning Capabilities of Language Models—0
Reasoning on Graphs: Faithful and Interpretable Large Language Model ReasoningCode1
Syllable-level lyrics generation from melody exploiting character-level language model—0
Large Language Model-Powered Smart Contract Vulnerability Detection: New PerspectivesCode1
UltraFeedback: Boosting Language Models with Scaled AI FeedbackCode3
GPT-Driver: Learning to Drive with GPTCode2
A Framework for Inference Inspired by Human Memory MechanismsCode1
Parameter-Efficient Tuning Helps Language Model Alignment—0
Meta Semantic Template for Evaluation of Large Language Models—0
SELF: Self-Evolution with Language Feedback—0
Adaptive-Solver Framework for Dynamic Strategy Selection in Large Language Model ReasoningCode0
Comics for Everyone: Generating Accessible Text Descriptions for Comic Strips—0
Faithful Explanations of Black-box NLP Models Using LLM-generated Counterfactuals—0
Empowering Many, Biasing a Few: Generalist Credit Scoring through Large Language ModelsCode1
Source Attribution for Large Language Model-Generated Data—0
UPAR: A Kantian-Inspired Prompting Framework for Enhancing Large Language Model Capabilities—0
NAYER: Noisy Layer Data Generation for Efficient and Effective Data-free Knowledge DistillationCode1
InstructCV: Instruction-Tuned Text-to-Image Diffusion Models as Vision GeneralistsCode2
AutomaTikZ: Text-Guided Synthesis of Scientific Vector Graphics with TikZCode1
Finding Pragmatic Differences Between Disciplines—0
PixArt-α: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image SynthesisCode4
SLM: Bridge the thin gap between speech and text foundation models—0
Evolving Diverse Red-team Language Models in Multi-round Multi-agent Games—0
Dynamic Demonstrations Controller for In-Context LearningCode0
From Language Modeling to Instruction Following: Understanding the Behavior Shift in LLMs after Instruction TuningCode1
Learning to Rewrite Prompts for Personalized Text Generation—0
Split and Merge: Aligning Position Biases in LLM-based Evaluators—0
Telling Stories for Common Sense Zero-Shot Action RecognitionCode0
LoRA ensembles for large language model fine-tuning—0
LLM-grounded Video Diffusion Models—0
Self-Specialization: Uncovering Latent Expertise within Large Language Models—0
AdaRefiner: Refining Decisions of Language Models with Adaptive FeedbackCode1
Motif: Intrinsic Motivation from Artificial Intelligence FeedbackCode1
Data Filtering NetworksCode3
A Large Language Model Approach to Educational Survey Feedback Analysis—0
Enhancing Code-switching Speech Recognition with Interactive Language Biases—0
Alphazero-like Tree-Search can Guide Large Language Model Decoding and TrainingCode2
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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