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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 9451–9500 of 17610 papers

TitleStatusHype
Beyond Text: Utilizing Vocal Cues to Improve Decision Making in LLMs for Robot Navigation Tasks—0
Adversarial Text Purification: A Large Language Model Approach for Defense—0
English Prompts are Better for NLI-based Zero-Shot Emotion Classification than Target-Language Prompts—0
Arabic Synonym BERT-based Adversarial Examples for Text ClassificationCode0
VLN-Video: Utilizing Driving Videos for Outdoor Vision-and-Language Navigation—0
Applying Unsupervised Semantic Segmentation to High-Resolution UAV Imagery for Enhanced Road Scene ParsingCode0
TexShape: Information Theoretic Sentence Embedding for Language ModelsCode0
LB-KBQA: Large-language-model and BERT based Knowledge-Based Question and Answering System—0
Nevermind: Instruction Override and Moderation in Large Language Models—0
Make Every Move Count: LLM-based High-Quality RTL Code Generation Using MCTS—0
Resolving Transcription Ambiguity in Spanish: A Hybrid Acoustic-Lexical System for Punctuation Restoration—0
RACER: An LLM-powered Methodology for Scalable Analysis of Semi-structured Mental Health InterviewsCode0
Learning from Teaching Regularization: Generalizable Correlations Should be Easy to Imitate—0
NetLLM: Adapting Large Language Models for Networking—0
Predicting Machine Translation Performance on Low-Resource Languages: The Role of Domain Similarity—0
Selecting Large Language Model to Fine-tune via Rectified Scaling LawCode0
Large Language Model for Table Processing: A Survey—0
The Developmental Landscape of In-Context Learning—0
Multi-modal Causal Structure Learning and Root Cause Analysis—0
BRAIn: Bayesian Reward-conditioned Amortized Inference for natural language generation from feedback—0
DeLLMa: Decision Making Under Uncertainty with Large Language Models—0
GLaPE: Gold Label-agnostic Prompt Evaluation and Optimization for Large Language ModelCode0
Can Large Language Models Learn Independent Causal Mechanisms?Code0
Generalizable Entity Grounding via Assistance of Large Language Model—0
GIRT-Model: Automated Generation of Issue Report TemplatesCode0
Analyzing Sentiment Polarity Reduction in News Presentation through Contextual Perturbation and Large Language Models—0
GPT-4V as Traffic Assistant: An In-depth Look at Vision Language Model on Complex Traffic Events—0
The Landscape and Challenges of HPC Research and LLMs—0
Panacea: Pareto Alignment via Preference Adaptation for LLMs—0
The Role of Foundation Models in Neuro-Symbolic Learning and Reasoning—0
K-Level Reasoning: Establishing Higher Order Beliefs in Large Language Models for Strategic Reasoning—0
Large Language Model Agent for Hyper-Parameter Optimization—0
Learning Semantic Information from Raw Audio Signal Using Both Contextual and Phonetic Representations—0
CorpusLM: Towards a Unified Language Model on Corpus for Knowledge-Intensive Tasks—0
Need a Small Specialized Language Model? Plan Early!—0
Leveraging Large Language Models for Analyzing Blood Pressure Variations Across Biological Sex from Scientific Literature—0
Rethinking the Role of Proxy Rewards in Language Model AlignmentCode0
Retrieval Augmented End-to-End Spoken Dialog Models—0
Deep Active Learning for Data Mining from Conflict Text Corpora—0
Integrating Large Language Models in Causal Discovery: A Statistical Causal ApproachCode0
BAT: Learning to Reason about Spatial Sounds with Large Language Models—0
Cross-modality debiasing: using language to mitigate sub-population shifts in imaging—0
Code Representation Learning At Scale—0
A Survey on Large Language Model Hallucination via a Creativity Perspective—0
What Will My Model Forget? Forecasting Forgotten Examples in Language Model Refinement—0
When Benchmarks are Targets: Revealing the Sensitivity of Large Language Model LeaderboardsCode0
Unlearnable Algorithms for In-context Learning—0
Transforming and Combining Rewards for Aligning Large Language Models—0
Investigating Recurrent Transformers with Dynamic HaltCode0
The Information of Large Language Model Geometry—0
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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