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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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

Showing 25512600 of 17610 papers

TitleStatusHype
MotionLLaMA: A Unified Framework for Motion Synthesis and ComprehensionCode2
Towards Agentic Schema Refinement0
DocEDA: Automated Extraction and Design of Analog Circuits from Documents with Large Language Model0
Tree Transformers are an Ineffective Model of Syntactic Constituency0
Enhancing Answer Reliability Through Inter-Model Consensus of Large Language Models0
StructFormer: Document Structure-based Masked Attention and its Impact on Language Model Pre-Training0
Functionality understanding and segmentation in 3D scenes0
SAGEval: The frontiers of Satisfactory Agent based NLG Evaluation for reference-free open-ended text0
VideoOrion: Tokenizing Object Dynamics in Videos0
When Babies Teach Babies: Can student knowledge sharing outperform Teacher-Guided Distillation on small datasets?Code0
BayLing 2: A Multilingual Large Language Model with Efficient Language AlignmentCode3
PromptHSI: Universal Hyperspectral Image Restoration with Vision-Language Modulated Frequency AdaptationCode1
VaLiD: Mitigating the Hallucination of Large Vision Language Models by Visual Layer Fusion Contrastive DecodingCode1
Can a Large Language Model Learn Matrix Functions In Context?Code0
Is Training Data Quality or Quantity More Impactful to Small Language Model Performance?Code0
Generative Prompt InternalizationCode0
Ensuring Fair LLM Serving Amid Diverse Applications0
Revelio: Interpreting and leveraging semantic information in diffusion modelsCode1
Multi-label Sequential Sentence Classification via Large Language ModelCode1
Steering Away from Harm: An Adaptive Approach to Defending Vision Language Model Against JailbreaksCode2
AfriMed-QA: A Pan-African, Multi-Specialty, Medical Question-Answering Benchmark Dataset0
From MTEB to MTOB: Retrieval-Augmented Classification for Descriptive GrammarsCode0
Semantic Shield: Defending Vision-Language Models Against Backdooring and Poisoning via Fine-grained Knowledge AlignmentCode0
Enabling Efficient Serverless Inference Serving for LLM (Large Language Model) in the Cloud0
MolMetaLM: a Physicochemical Knowledge-Guided Molecular Meta Language ModelCode0
Automatic High-quality Verilog Assertion Generation through Subtask-Focused Fine-Tuned LLMs and Iterative Prompting0
Large Language Model with Region-guided Referring and Grounding for CT Report GenerationCode2
Effective SAM Combination for Open-Vocabulary Semantic Segmentation0
Astro-HEP-BERT: A bidirectional language model for studying the meanings of concepts in astrophysics and high energy physics0
ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long VideosCode1
RE-Bench: Evaluating frontier AI R&D capabilities of language model agents against human expertsCode2
The BS-meter: A ChatGPT-Trained Instrument to Detect Sloppy Language-Games0
Tulu 3: Pushing Frontiers in Open Language Model Post-TrainingCode7
ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation0
ScribeAgent: Towards Specialized Web Agents Using Production-Scale Workflow DataCode2
GMAI-VL & GMAI-VL-5.5M: A Large Vision-Language Model and A Comprehensive Multimodal Dataset Towards General Medical AICode2
Planning-Driven Programming: A Large Language Model Programming WorkflowCode1
Memory Backdoor Attacks on Neural Networks0
Tiny-Align: Bridging Automatic Speech Recognition and Large Language Model on the Edge0
PIORS: Personalized Intelligent Outpatient Reception based on Large Language Model with Multi-Agents Medical Scenario SimulationCode0
UnifiedCrawl: Aggregated Common Crawl for Affordable Adaptation of LLMs on Low-Resource LanguagesCode1
Schemato -- An LLM for Netlist-to-Schematic Conversion0
Why do language models perform worse for morphologically complex languages?Code1
DRPruning: Efficient Large Language Model Pruning through Distributionally Robust OptimizationCode0
A Framework for Evaluating LLMs Under Task Indeterminacy0
SemiKong: Curating, Training, and Evaluating A Semiconductor Industry-Specific Large Language ModelCode3
Beyond Visual Understanding: Introducing PARROT-360V for Vision Language Model Benchmarking0
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and ChemistryCode0
S^2ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning0
Multimodal large language model for wheat breeding: a new exploration of smart breeding0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Decay RNNValidation perplexity76.67Unverified
2GRUValidation perplexity53.78Unverified
3LSTMValidation perplexity52.73Unverified
4LSTMTest perplexity48.7Unverified
5Temporal CNNTest perplexity45.2Unverified
6TCNTest perplexity45.19Unverified
7GCNN-8Test perplexity44.9Unverified
8Neural cache model (size = 100)Test perplexity44.8Unverified
9Neural cache model (size = 2,000)Test perplexity40.8Unverified
10GPT-2 SmallTest perplexity37.5Unverified
#ModelMetricClaimedVerifiedStatus
1TCNTest perplexity108.47Unverified
2Seq-U-NetTest perplexity107.95Unverified
3GRU (Bai et al., 2018)Test perplexity92.48Unverified
4R-TransformerTest perplexity84.38Unverified
5Zaremba et al. (2014) - LSTM (medium)Test perplexity82.7Unverified
6Gal & Ghahramani (2016) - Variational LSTM (medium)Test perplexity79.7Unverified
7LSTM (Bai et al., 2018)Test perplexity78.93Unverified
8Zaremba et al. (2014) - LSTM (large)Test perplexity78.4Unverified
9Gal & Ghahramani (2016) - Variational LSTM (large)Test perplexity75.2Unverified
10Inan et al. (2016) - Variational RHNTest perplexity66Unverified
#ModelMetricClaimedVerifiedStatus
1LSTM (7 layers)Bit per Character (BPC)1.67Unverified
2HypernetworksBit per Character (BPC)1.34Unverified
3SHA-LSTM (4 layers, h=1024, no attention head)Bit per Character (BPC)1.33Unverified
4LN HM-LSTMBit per Character (BPC)1.32Unverified
5ByteNetBit per Character (BPC)1.31Unverified
6Recurrent Highway NetworksBit per Character (BPC)1.27Unverified
7Large FS-LSTM-4Bit per Character (BPC)1.25Unverified
8Large mLSTMBit per Character (BPC)1.24Unverified
9AWD-LSTM (3 layers)Bit per Character (BPC)1.23Unverified
10Cluster-Former (#C=512)Bit per Character (BPC)1.22Unverified
#ModelMetricClaimedVerifiedStatus
1Smaller Transformer 126M (pre-trained)Test perplexity33Unverified
2OPT 125MTest perplexity32.26Unverified
3Larger Transformer 771M (pre-trained)Test perplexity28.1Unverified
4OPT 1.3BTest perplexity19.55Unverified
5GPT-Neo 125MTest perplexity17.83Unverified
6OPT 2.7BTest perplexity17.81Unverified
7Smaller Transformer 126M (fine-tuned)Test perplexity12Unverified
8GPT-Neo 1.3BTest perplexity11.46Unverified
9Transformer 125MTest perplexity10.7Unverified
10GPT-Neo 2.7BTest perplexity10.44Unverified