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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 5201–5250 of 17610 papers

TitleStatusHype
Dragonfly: Multi-Resolution Zoom-In Encoding Enhances Vision-Language ModelsCode2
Luna: An Evaluation Foundation Model to Catch Language Model Hallucinations with High Accuracy and Low Cost—0
Helix: Serving Large Language Models over Heterogeneous GPUs and Network via Max-FlowCode2
The Geometry of Categorical and Hierarchical Concepts in Large Language ModelsCode2
Understanding Token Probability Encoding in Output Embeddings—0
MultiMax: Sparse and Multi-Modal Attention LearningCode1
HBTP: Heuristic Behavior Tree Planning with Large Language Model ReasoningCode0
Towards a copilot in BIM authoring tool using a large language model-based agent for intelligent human-machine interaction—0
Harnessing Business and Media Insights with Large Language Models—0
Inverse Constitutional AI: Compressing Preferences into PrinciplesCode1
Distortion-free Watermarks are not Truly Distortion-free under Watermark Key Collisions—0
Aligning Language Models with Demonstrated FeedbackCode2
LongSkywork: A Training Recipe for Efficiently Extending Context Length in Large Language Models—0
FOCUS: Forging Originality through Contrastive Use in Self-Plagiarism for Language Models—0
Large Language Model Confidence Estimation via Black-Box Access—0
Wav2Prompt: End-to-End Speech Prompt Generation and Tuning For LLM in Zero and Few-shot Learning—0
HonestLLM: Toward an Honest and Helpful Large Language ModelCode1
Controlling Large Language Model Agents with Entropic Activation Steering—0
KGLink: A column type annotation method that combines knowledge graph and pre-trained language modelCode0
On Overcoming Miscalibrated Conversational Priors in LLM-based Chatbots—0
HENASY: Learning to Assemble Scene-Entities for Egocentric Video-Language Model—0
InterpreTabNet: Distilling Predictive Signals from Tabular Data by Salient Feature InterpretationCode1
RAG Does Not Work for Enterprises—0
LOLAMEME: Logic, Language, Memory, Mechanistic Framework—0
DYNA: Disease-Specific Language Model for Variant Pathogenicity—0
Query2CAD: Generating CAD models using natural language queriesCode2
LLM-RankFusion: Mitigating Intrinsic Inconsistency in LLM-based RankingCode0
Self-Augmented Preference Optimization: Off-Policy Paradigms for Language Model AlignmentCode0
StrucTexTv3: An Efficient Vision-Language Model for Text-rich Image Perception, Comprehension, and Beyond—0
Masked Language Modeling Becomes Conditional Density Estimation for Tabular Data Synthesis—0
ABodyBuilder3: Improved and scalable antibody structure predictionsCode2
MeshXL: Neural Coordinate Field for Generative 3D Foundation ModelsCode3
Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space DualityCode11
FineRadScore: A Radiology Report Line-by-Line Evaluation Technique Generating Corrections with Severity Scores—0
Exploratory Preference Optimization: Harnessing Implicit Q*-Approximation for Sample-Efficient RLHF—0
Kaleido Diffusion: Improving Conditional Diffusion Models with Autoregressive Latent Modeling—0
You Only Scan Once: Efficient Multi-dimension Sequential Modeling with LightNet—0
Evaluating Large Language Model Biases in Persona-Steered GenerationCode0
CycleFormer : TSP Solver Based on Language ModelingCode1
Automated Generation and Tagging of Knowledge Components from Multiple-Choice QuestionsCode0
SeamlessExpressiveLM: Speech Language Model for Expressive Speech-to-Speech Translation with Chain-of-Thought—0
Towards Ontology-Enhanced Representation Learning for Large Language ModelsCode0
Who Writes the Review, Human or AI?—0
Would I Lie To You? Inference Time Alignment of Language Models using Direct Preference HeadsCode0
Knowledge-grounded Adaptation Strategy for Vision-language Models: Building Unique Case-set for Screening Mammograms for Residents Training—0
From Words to Actions: Unveiling the Theoretical Underpinnings of LLM-Driven Autonomous Systems—0
GNN-RAG: Graph Neural Retrieval for Large Language Model ReasoningCode3
Sequence-Augmented SE(3)-Flow Matching For Conditional Protein Backbone GenerationCode3
Detecting Hallucinations in Large Language Model Generation: A Token Probability ApproachCode1
Quest: Query-centric Data Synthesis Approach for Long-context Scaling of Large Language ModelCode1
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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