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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 2601–2650 of 17610 papers

TitleStatusHype
S^2ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning—0
Robust Planning with Compound LLM Architectures: An LLM-Modulo ApproachCode1
Watermark under Fire: A Robustness Evaluation of LLM WatermarkingCode0
Unlocking Historical Clinical Trial Data with ALIGN: A Compositional Large Language Model System for Medical Coding—0
MERLOT: A Distilled LLM-based Mixture-of-Experts Framework for Scalable Encrypted Traffic Classification—0
Compute Optimal Inference and Provable Amortisation Gap in Sparse Autoencoders—0
Patience Is The Key to Large Language Model Reasoning—0
Existential Conversations with Large Language Models: Content, Community, and Culture—0
Advancing Complex Medical Communication in Arabic with Sporo AraSum: Surpassing Existing Large Language Models—0
Ranking Unraveled: Recipes for LLM Rankings in Head-to-Head AI CombatCode0
StreetviewLLM: Extracting Geographic Information Using a Chain-of-Thought Multimodal Large Language Model—0
Selective Attention: Enhancing Transformer through Principled Context ControlCode1
Med-2E3: A 2D-Enhanced 3D Medical Multimodal Large Language Model—0
RadPhi-3: Small Language Models for Radiology—0
Probing the Capacity of Language Model Agents to Operationalize Disparate Experiential Context Despite DistractionCode0
A Layered Architecture for Developing and Enhancing Capabilities in Large Language Model-based Software Systems—0
CUE-M: Contextual Understanding and Enhanced Search with Multimodal Large Language Model—0
Unlocking State-Tracking in Linear RNNs Through Negative EigenvaluesCode1
HouseLLM: LLM-Assisted Two-Phase Text-to-Floorplan Generation—0
Generative Timelines for Instructed Visual Assembly—0
Strengthening Fake News Detection: Leveraging SVM and Sophisticated Text Vectorization Techniques. Defying BERT?—0
CATCH: Complementary Adaptive Token-level Contrastive Decoding to Mitigate Hallucinations in LVLMs—0
Large Language Model for Qualitative Research -- A Systematic Mapping Study—0
Improved GUI Grounding via Iterative NarrowingCode1
Does Unlearning Truly Unlearn? A Black Box Evaluation of LLM Unlearning MethodsCode0
VL-Uncertainty: Detecting Hallucination in Large Vision-Language Model via Uncertainty EstimationCode0
ByteScience: Bridging Unstructured Scientific Literature and Structured Data with Auto Fine-tuned Large Language Model in Token Granularity—0
Leveraging MLLM Embeddings and Attribute Smoothing for Compositional Zero-Shot LearningCode1
Mitigating Gender Bias in Contextual Word Embeddings—0
Addressing Hallucinations in Language Models with Knowledge Graph Embeddings as an Additional Modality—0
Mitigating Knowledge Conflicts in Language Model-Driven Question Answering—0
MC-LLaVA: Multi-Concept Personalized Vision-Language ModelCode2
PSA-VLM: Enhancing Vision-Language Model Safety through Progressive Concept-Bottleneck-Driven Alignment—0
TrojanRobot: Physical-World Backdoor Attacks Against VLM-based Robotic Manipulation—0
Topology-aware Preemptive Scheduling for Co-located LLM WorkloadsCode0
Large corpora and large language models: a replicable method for automating grammatical annotation—0
Steering Language Model Refusal with Sparse Autoencoders—0
Bi-Mamba: Towards Accurate 1-Bit State Space Models—0
Preempting Text Sanitization Utility in Resource-Constrained Privacy-Preserving LLM InteractionsCode0
AddrLLM: Address Rewriting via Large Language Model on Nationwide Logistics Data—0
Analyzing Pokémon and Mario Streamers' Twitch Chat with LLM-based User Embeddings—0
Learn from Downstream and Be Yourself in Multimodal Large Language Model Fine-TuningCode0
BianCang: A Traditional Chinese Medicine Large Language ModelCode2
Improving training time and GPU utilization in geo-distributed language model training—0
VayuBuddy: an LLM-Powered Chatbot to Democratize Air Quality Insights—0
A Novel Approach to Eliminating Hallucinations in Large Language Model-Assisted Causal Discovery—0
GeoGround: A Unified Large Vision-Language Model for Remote Sensing Visual GroundingCode2
MpoxVLM: A Vision-Language Model for Diagnosing Skin Lesions from Mpox Virus InfectionCode0
MetaLA: Unified Optimal Linear Approximation to Softmax Attention MapCode1
Multi-Stage Vision Token Dropping: Towards Efficient Multimodal 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