Papers Large Language Model
“Large Language Model” 태그가 달린 논문 6,097편 · 필터 해제
SpatialLM: Training Large Language Models for Structured Indoor Modeling
SpatialLM is a large language model designed to process 3D point cloud data and generate structured 3D scene understanding outputs. These outputs include architectural elements like walls, doors, windows, and oriented ob…
3D Object DetectionLanguage ModelingLanguage ModellingLarge Language Model+3Language-Grounded Hierarchical Planning and Execution with Multi-Robot 3D Scene Graphs
In this paper, we introduce a multi-robot system that integrates mapping, localization, and task and motion planning (TAMP) enabled by 3D scene graphs to execute complex instructions expressed in natural language. Our sy…
Language ModelingLanguage ModellingLarge Language ModelMotion Planning+1LLM Unlearning Should Be Form-Independent
Large Language Model (LLM) unlearning aims to erase or suppress undesirable knowledge within the model, offering promise for controlling harmful or private information to prevent misuse. However, recent studies highlight…
FormLarge Language ModelJavelinGuard: Low-Cost Transformer Architectures for LLM Security
We present JavelinGuard, a suite of low-cost, high-performance model architectures designed for detecting malicious intent in Large Language Model (LLM) interactions, optimized specifically for production deployment. Rec…
CPULarge Language ModelG-Memory: Tracing Hierarchical Memory for Multi-Agent Systems
Large language model (LLM)-powered multi-agent systems (MAS) have demonstrated cognitive and execution capabilities that far exceed those of single LLM agents, yet their capacity for self-evolution remains hampered by un…
Large Language ModelSpeech Recognition on TV Series with Video-guided Post-Correction
Automatic Speech Recognition (ASR) has achieved remarkable success with deep learning, driving advancements in conversational artificial intelligence, media transcription, and assistive technologies. However, ASR systems…
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)Large Language Modelspeech-recognition+1AnnoDPO: Protein Functional Annotation Learning with Direct Preference Optimization
Deciphering protein function remains a fundamental challenge in protein representation learning. The task presents significant difficulties for protein language models (PLMs) due to the sheer volume of functional annotat…
Language ModelingLanguage ModellingLarge Language ModelProtein Function Prediction+1RoboPARA: Dual-Arm Robot Planning with Parallel Allocation and Recomposition Across Tasks
Dual-arm robots play a crucial role in improving efficiency and flexibility in complex multitasking scenarios. While existing methods have achieved promising results in task planning, they often fail to fully optimize ta…
Large Language ModelTask PlanningAn Agentic Framework for Autonomous Metamaterial Modeling and Inverse Design
Recent significant advances in integrating multiple Large Language Model (LLM) systems have enabled Agentic Frameworks capable of performing complex tasks autonomously, including novel scientific research. We develop and…
Language ModelingLanguage ModellingLarge Language ModelContextual Experience Replay for Self-Improvement of Language Agents
Large language model (LLM) agents have been applied to sequential decision-making tasks such as web navigation, but without any environment-specific experiences, they often fail in these complex tasks. Moreover, current …
Decision MakingLarge Language ModelSequential Decision MakingEigenspectrum Analysis of Neural Networks without Aspect Ratio Bias
Diagnosing deep neural networks (DNNs) through the eigenspectrum of weight matrices has been an active area of research in recent years. At a high level, eigenspectrum analysis of DNNs involves measuring the heavytailnes…
image-classificationImage ClassificationLarge Language ModelVoice Impression Control in Zero-Shot TTS
Para-/non-linguistic information in speech is pivotal in shaping the listeners' impression. Although zero-shot text-to-speech (TTS) has achieved high speaker fidelity, modulating subtle para-/non-linguistic information t…
Language ModelingLanguage ModellingLarge Language Modeltext-to-speech+1HeavyWater and SimplexWater: Watermarking Low-Entropy Text Distributions
Large language model (LLM) watermarks enable authentication of text provenance, curb misuse of machine-generated text, and promote trust in AI systems. Current watermarks operate by changing the next-token predictions ou…
Large Language ModelText GenerationTraining-Free Query Optimization via LLM-Based Plan Similarity
Large language model (LLM) embeddings offer a promising new avenue for database query optimization. In this paper, we explore how pre-trained execution plan embeddings can guide SQL query execution without the need for a…
Language ModelingLanguage ModellingLarge Language ModelCost-Efficient LLM Training with Lifetime-Aware Tensor Offloading via GPUDirect Storage
We present the design and implementation of a new lifetime-aware tensor offloading framework for GPU memory expansion using low-cost PCIe-based solid-state drives (SSDs). Our framework, TERAIO, is developed explicitly fo…
CPUGPULarge Language ModelScriptDoctor: Automatic Generation of PuzzleScript Games via Large Language Models and Tree Search
There is much interest in using large pre-trained models in Automatic Game Design (AGD), whether via the generation of code, assets, or more abstract conceptualization of design ideas. But so far this interest largely st…
Game DesignLarge Language ModelHierarchical Debate-Based Large Language Model (LLM) for Complex Task Planning of 6G Network Management
6G networks have become increasingly complicated due to novel network architecture and newly emerging signal processing and transmission techniques, leading to significant burdens to 6G network management. Large language…
Language ModelingLanguage ModellingLarge Language ModelManagement+1Prompting Wireless Networks: Reinforced In-Context Learning for Power Control
To manage and optimize constantly evolving wireless networks, existing machine learning (ML)- based studies operate as black-box models, leading to increased computational costs during training and a lack of transparency…
Decision MakingIn-Context LearningLarge Language ModelReinforcement Learning (RL)SPARQ: Synthetic Problem Generation for Reasoning via Quality-Diversity Algorithms
Large language model (LLM) driven synthetic data generation has emerged as a powerful method for improving model reasoning capabilities. However, most methods either distill large state-of-the-art models into small stude…
DiversityLarge Language ModelMathSynthetic Data GenerationDAM: Dynamic Attention Mask for Long-Context Large Language Model Inference Acceleration
Long-context understanding is crucial for many NLP applications, yet transformers struggle with efficiency due to the quadratic complexity of self-attention. Sparse attention methods alleviate this cost but often impose …
Computational EfficiencyLanguage ModelingLanguage ModellingLarge Language Model+2