Papers Language Modeling
“Language Modeling” 태그가 달린 논문 14,182편 · 필터 해제
Visual-Language Model Knowledge Distillation Method for Image Quality Assessment
Image Quality Assessment (IQA) is a core task in computer vision. Multimodal methods based on vision-language models, such as CLIP, have demonstrated exceptional generalization capabilities in IQA tasks. To address the i…
Image Quality AssessmentKnowledge DistillationLanguage ModelingLanguage ModellingMaking Language Model a Hierarchical Classifier and Generator
Decoder-only language models, such as GPT and LLaMA, generally decode on the last layer. Motivated by human's hierarchical thinking capability, we propose that a hierarchical decoder architecture could be built with diff…
DecoderLanguage ModelingLanguage Modellingmodel+3VisionThink: Smart and Efficient Vision Language Model via Reinforcement Learning
Recent advancements in vision-language models (VLMs) have improved performance by increasing the number of visual tokens, which are often significantly longer than text tokens. However, we observe that most real-world sc…
Language ModelingLanguage ModellingOptical Character Recognition (OCR)reinforcement-learning+2The Generative Energy Arena (GEA): Incorporating Energy Awareness in Large Language Model (LLM) Human Evaluations
The evaluation of large language models is a complex task, in which several approaches have been proposed. The most common is the use of automated benchmarks in which LLMs have to answer multiple-choice questions of diff…
Language ModelingLanguage ModellingLarge Language ModelMultiple-choiceInverse Reinforcement Learning Meets Large Language Model Post-Training: Basics, Advances, and Opportunities
In the era of Large Language Models (LLMs), alignment has emerged as a fundamental yet challenging problem in the pursuit of more reliable, controllable, and capable machine intelligence. The recent success of reasoning …
Language ModelingLanguage ModellingLarge Language ModelReinforcement Learning (RL)Assay2Mol: large language model-based drug design using BioAssay context
Scientific databases aggregate vast amounts of quantitative data alongside descriptive text. In biochemistry, molecule screening assays evaluate the functional responses of candidate molecules against disease targets. Un…
DescriptiveDrug DesignDrug DiscoveryIn-Context Learning+3Describe Anything Model for Visual Question Answering on Text-rich Images
Recent progress has been made in region-aware vision-language modeling, particularly with the emergence of the Describe Anything Model (DAM). DAM is capable of generating detailed descriptions of any specific image areas…
DescriptiveLanguage ModelingLanguage ModellingQuestion Answering+2InstructFLIP: Exploring Unified Vision-Language Model for Face Anti-spoofing
Face anti-spoofing (FAS) aims to construct a robust system that can withstand diverse attacks. While recent efforts have concentrated mainly on cross-domain generalization, two significant challenges persist: limited sem…
Domain GeneralizationFace Anti-SpoofingLanguage ModelingLanguage ModellingIs This Just Fantasy? Language Model Representations Reflect Human Judgments of Event Plausibility
Language models (LMs) are used for a diverse range of tasks, from question answering to writing fantastical stories. In order to reliably accomplish these tasks, LMs must be able to discern the modal category of a senten…
Language ModelingLanguage ModellingQuestion AnsweringKptLLM++: Towards Generic Keypoint Comprehension with Large Language Model
The emergence of Multimodal Large Language Models (MLLMs) has revolutionized image understanding by bridging textual and visual modalities. However, these models often struggle with capturing fine-grained semantic inform…
Keypoint DetectionLanguage ModelingLanguage ModellingLarge Language Model+1Tactical Decision for Multi-UGV Confrontation with a Vision-Language Model-Based Commander
In multiple unmanned ground vehicle confrontations, autonomously evolving multi-agent tactical decisions from situational awareness remain a significant challenge. Traditional handcraft rule-based methods become vulnerab…
Language ModelingLanguage ModellingLarge Language Modelreinforcement-learning+2Mixture of Experts in Large Language Models
This paper presents a comprehensive review of the Mixture-of-Experts (MoE) architecture in large language models, highlighting its ability to significantly enhance model performance while maintaining minimal computationa…
DiversityLanguage ModelingLanguage ModellingLarge Language Model+2LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification
Verifying the credibility of Cyber Threat Intelligence (CTI) is essential for reliable cybersecurity defense. However, traditional approaches typically treat this task as a static classification problem, relying on handc…
Language ModelingLanguage ModellingLarge Language ModelNatural Language Inference+1LiLM-RDB-SFC: Lightweight Language Model with Relational Database-Guided DRL for Optimized SFC Provisioning
Effective management of Service Function Chains (SFCs) and optimal Virtual Network Function (VNF) placement are critical challenges in modern Software-Defined Networking (SDN) and Network Function Virtualization (NFV) en…
Deep Reinforcement LearningLanguage ModelingLanguage ModellingLarge Language ModelKisMATH: Do LLMs Have Knowledge of Implicit Structures in Mathematical Reasoning?
Chain-of-thought traces have been shown to improve performance of large language models in a plethora of reasoning tasks, yet there is no consensus on the mechanism through which this performance boost is achieved. To sh…
GSM8KLanguage ModelingLanguage ModellingMathematical ReasoningMLAR: Multi-layer Large Language Model-based Robotic Process Automation Applicant Tracking
This paper introduces an innovative Applicant Tracking System (ATS) enhanced by a novel Robotic process automation (RPA) framework or as further referred to as MLAR. Traditional recruitment processes often encounter bott…
BenchmarkingLanguage ModelingLanguage ModellingLarge Language ModelIceberg: Enhancing HLS Modeling with Synthetic Data
Deep learning-based prediction models for High-Level Synthesis (HLS) of hardware designs often struggle to generalize. In this paper, we study how to close the generalizability gap of these models through pretraining on …
Data AugmentationHigh-Level SynthesisLanguage ModelingLanguage Modelling+2Kodezi Chronos: A Debugging-First Language Model for Repository-Scale, Memory-Driven Code Understanding
Large Language Models (LLMs) have advanced code generation and software automation, but are fundamentally constrained by limited inference-time context and lack of explicit code structure reasoning. We introduce Kodezi C…
Code GenerationLanguage ModelingLanguage ModellingRetrievalByDeWay: Boost Your multimodal LLM with DEpth prompting in a Training-Free Way
We introduce ByDeWay, a training-free framework designed to enhance the performance of Multimodal Large Language Models (MLLMs). ByDeWay uses a novel prompting strategy called Layered-Depth-Based Prompting (LDP), which i…
Depth EstimationHallucinationLanguage ModelingLanguage Modelling+2Lizard: An Efficient Linearization Framework for Large Language Models
We propose Lizard, a linearization framework that transforms pretrained Transformer-based Large Language Models (LLMs) into flexible, subquadratic architectures for infinite-context generation. Transformer-based LLMs fac…
Language ModelingLanguage ModellingMMLU