Papers Large Language Model
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ARAG: Agentic Retrieval Augmented Generation for Personalized Recommendation
Retrieval-Augmented Generation (RAG) has shown promise in enhancing recommendation systems by incorporating external context into large language model prompts. However, existing RAG-based approaches often rely on static …
Large Language ModelNatural Language InferenceRAGRecommendation Systems+2A Large Language Model-Empowered Agent for Reliable and Robust Structural Analysis
Large language models (LLMs) have exhibited remarkable capabilities across diverse open-domain tasks, yet their application in specialized domains such as civil engineering remains largely unexplored. This paper starts b…
Code GenerationLanguage ModelingLanguage ModellingLarge Language ModelPsyLite Technical Report
With the rapid development of digital technology, AI-driven psychological counseling has gradually become an important research direction in the field of mental health. However, existing models still have deficiencies in…
Large Language ModelLightweight DeploymentQuantizationRAGLLM-guided Chemical Process Optimization with a Multi-Agent Approach
Chemical process optimization is crucial to maximize production efficiency and economic performance. Traditional methods, including gradient-based solvers, evolutionary algorithms, and parameter grid searches, become imp…
Chemical ProcessComputational EfficiencyEvolutionary AlgorithmsLarge Language ModelThinkSound: Chain-of-Thought Reasoning in Multimodal Large Language Models for Audio Generation and Editing
While end-to-end video-to-audio generation has greatly improved, producing high-fidelity audio that authentically captures the nuances of visual content remains challenging. Like professionals in the creative industries,…
Audio GenerationLarge Language ModelMultimodal Large Language ModelPrompt-Guided Turn-Taking Prediction
Turn-taking prediction models are essential components in spoken dialogue systems and conversational robots. Recent approaches leverage transformer-based architectures to predict speech activity continuously and in real-…
Language ModelingLanguage ModellingLarge Language ModelPrediction+1MedPrompt: LLM-CNN Fusion with Weight Routing for Medical Image Segmentation and Classification
Current medical image analysis systems are typically task-specific, requiring separate models for classification and segmentation, and lack the flexibility to support user-defined workflows. To address these challenges, …
Image SegmentationLarge Language ModelMedical Image AnalysisMedical Image Segmentation+2Multimodal Prompt Alignment for Facial Expression Recognition
Prompt learning has been widely adopted to efficiently adapt vision-language models (VLMs) like CLIP for various downstream tasks. Despite their success, current VLM-based facial expression recognition (FER) methods stru…
Facial Expression RecognitionFacial Expression Recognition (FER)Large Language ModelPrompt LearningOracleFusion: Assisting the Decipherment of Oracle Bone Script with Structurally Constrained Semantic Typography
As one of the earliest ancient languages, Oracle Bone Script (OBS) encapsulates the cultural records and intellectual expressions of ancient civilizations. Despite the discovery of approximately 4,500 OBS characters, onl…
DeciphermentLarge Language ModelMultimodal Large Language ModelVisual LocalizationGroundFlow: A Plug-in Module for Temporal Reasoning on 3D Point Cloud Sequential Grounding
Sequential grounding in 3D point clouds (SG3D) refers to locating sequences of objects by following text instructions for a daily activity with detailed steps. Current 3D visual grounding (3DVG) methods treat text instru…
3D visual groundingLarge Language ModelVisual GroundingHumanOmniV2: From Understanding to Omni-Modal Reasoning with Context
With the rapid evolution of multimodal large language models, the capacity to deeply understand and interpret human intentions has emerged as a critical capability, which demands detailed and thoughtful reasoning. In rec…
Large Language ModelMultimodal ReasoningReinforcement Learning (RL)Detecting Referring Expressions in Visually Grounded Dialogue with Autoregressive Language Models
In this paper, we explore the use of a text-only, autoregressive language modeling approach for the extraction of referring expressions from visually grounded dialogue. More specifically, the aim is to investigate the ex…
Language ModelingLanguage ModellingLarge Language Modelparameter-efficient fine-tuning+1mTSBench: Benchmarking Multivariate Time Series Anomaly Detection and Model Selection at Scale
Multivariate time series anomaly detection (MTS-AD) is critical in domains like healthcare, cybersecurity, and industrial monitoring, yet remains challenging due to complex inter-variable dependencies, temporal dynamics,…
Anomaly DetectionBenchmarkingLanguage ModelingLanguage Modelling+4MT2-CSD: A New Dataset and Multi-Semantic Knowledge Fusion Method for Conversational Stance Detection
In the realm of contemporary social media, automatic stance detection is pivotal for opinion mining, as it synthesizes and examines user perspectives on contentious topics to uncover prevailing trends and sentiments. Tra…
Large Language ModelOpinion MiningStance DetectionWhere to find Grokking in LLM Pretraining? Monitor Memorization-to-Generalization without Test
Grokking, i.e., test performance keeps improving long after training loss converged, has been recently witnessed in neural network training, making the mechanism of generalization and other emerging capabilities such as …
Code GenerationLarge Language ModelMathMemorizationCan "consciousness" be observed from large language model (LLM) internal states? Dissecting LLM representations obtained from Theory of Mind test with Integrated Information Theory and Span Representation analysis
Integrated Information Theory (IIT) provides a quantitative framework for explaining consciousness phenomenon, positing that conscious systems comprise elements integrated through causal properties. We apply IIT 3.0 and …
Explainable Artificial Intelligence (XAI)Interpretable Machine LearningLanguage ModelingLanguage Modelling+1AgentStealth: Reinforcing Large Language Model for Anonymizing User-generated Text
In today's digital world, casual user-generated content often contains subtle cues that may inadvertently expose sensitive personal attributes. Such risks underscore the growing importance of effective text anonymization…
Contrastive LearningLanguage ModelingLanguage ModellingLarge Language Model+1Large Language Model Agent for Modular Task Execution in Drug Discovery
We present a modular framework powered by large language models (LLMs) that automates and streamlines key tasks across the early-stage computational drug discovery pipeline. By combining LLM reasoning with domain-specifi…
Drug DiscoveryLanguage ModelingLanguage ModellingLarge Language Model+2Enterprise Large Language Model Evaluation Benchmark
Large Language Models (LLMs) ) have demonstrated promise in boosting productivity across AI-powered tools, yet existing benchmarks like Massive Multitask Language Understanding (MMLU) inadequately assess enterprise-speci…
Language Model EvaluationLanguage ModelingLanguage ModellingLarge Language Model+4Case-based Reasoning Augmented Large Language Model Framework for Decision Making in Realistic Safety-Critical Driving Scenarios
Driving in safety-critical scenarios requires quick, context-aware decision-making grounded in both situational understanding and experiential reasoning. Large Language Models (LLMs), with their powerful general-purpose …
Autonomous DrivingDecision MakingDomain AdaptationIn-Context Learning+5