Papers Large Language Model
“Large Language Model” 태그가 달린 논문 6,097편 · 필터 해제
Iceberg: 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+2PoseLLM: Enhancing Language-Guided Human Pose Estimation with MLP Alignment
Human pose estimation traditionally relies on architectures that encode keypoint priors, limiting their generalization to novel poses or unseen keypoints. Recent language-guided approaches like LocLLM reformulate keypoin…
Large Language ModelPose EstimationZero-shot GeneralizationKAT-V1: Kwai-AutoThink Technical Report
We present Kwaipilot-AutoThink (KAT), an open-source 40B large language model developed to address the overthinking problem in reasoning-intensive tasks, where an automatic thinking training paradigm is proposed to dynam…
Knowledge DistillationLarge Language ModelMixture-of-ExpertsDynamic Parameter Memory: Temporary LoRA-Enhanced LLM for Long-Sequence Emotion Recognition in Conversation
Recent research has focused on applying speech large language model (SLLM) to improve speech emotion recognition (SER). However, the inherently high frame rate in speech modality severely limits the signal processing and…
4kEmotion RecognitionEmotion Recognition in ConversationLarge Language Model+2SAND: Boosting LLM Agents with Self-Taught Action Deliberation
Large Language Model (LLM) agents are commonly tuned with supervised finetuning on ReAct-style expert trajectories or preference optimization over pairwise rollouts. Most of these methods focus on imitating specific expe…
Large Language ModelSandSkip a Layer or Loop it? Test-Time Depth Adaptation of Pretrained LLMs
Can a pretrained neural network adapt its architecture to different inputs without any finetuning? Do we need all layers for simple tasks, and are they adequate for challenging tasks? We found that the layers of a pretra…
CoLALarge Language ModelMathGNN-ViTCap: GNN-Enhanced Multiple Instance Learning with Vision Transformers for Whole Slide Image Classification and Captioning
Microscopic assessment of histopathology images is vital for accurate cancer diagnosis and treatment. Whole Slide Image (WSI) classification and captioning have become crucial tasks in computer-aided pathology. However, …
Caption GenerationClusteringGraph Neural Networkimage-classification+3Open Source Planning & Control System with Language Agents for Autonomous Scientific Discovery
We present a multi-agent system for automation of scientific research tasks, cmbagent. The system is formed by about 30 Large Language Model (LLM) agents and implements a Planning & Control strategy to orchestrate the ag…
Language ModelingLanguage ModellingLarge Language Modelscientific discoveryBilateral Collaboration with Large Vision-Language Models for Open Vocabulary Human-Object Interaction Detection
Open vocabulary Human-Object Interaction (HOI) detection is a challenging task that detects all <human, verb, object> triplets of interest in an image, even those that are not pre-defined in the training set. Existing ap…
Human-Object Interaction DetectionLarge Language ModelSqueeze the Soaked Sponge: Efficient Off-policy Reinforcement Finetuning for Large Language Model
Reinforcement Learning (RL) has demonstrated its potential to improve the reasoning ability of Large Language Models (LLMs). One major limitation of most existing Reinforcement Finetuning (RFT) methods is that they are o…
Language ModelingLanguage ModellingLarge Language ModelMath+1A Neural Representation Framework with LLM-Driven Spatial Reasoning for Open-Vocabulary 3D Visual Grounding
Open-vocabulary 3D visual grounding aims to localize target objects based on free-form language queries, which is crucial for embodied AI applications such as autonomous navigation, robotics, and augmented reality. Learn…
3D visual groundingAutonomous NavigationLarge Language ModelSpatial Reasoning+1The Dark Side of LLMs Agent-based Attacks for Complete Computer Takeover
The rapid adoption of Large Language Model (LLM) agents and multi-agent systems enables unprecedented capabilities in natural language processing and generation. However, these systems have introduced unprecedented secur…
Large Language ModelRAGPrefixAgent: An LLM-Powered Design Framework for Efficient Prefix Adder Optimization
Prefix adders are fundamental arithmetic circuits, but their design space grows exponentially with bit-width, posing significant optimization challenges. Previous works face limitations in performance, generalization, an…
Language ModelingLanguage ModellingLarge Language ModelRecRankerEval: A Flexible and Extensible Framework for Top-k LLM-based Recommendation
A recent Large language model (LLM)-based recommendation model, called RecRanker, has demonstrated a superior performance in the top-k recommendation task compared to other models. In particular, RecRanker samples users …
Large Language ModelCAVGAN: Unifying Jailbreak and Defense of LLMs via Generative Adversarial Attacks on their Internal Representations
Security alignment enables the Large Language Model (LLM) to gain the protection against malicious queries, but various jailbreak attack methods reveal the vulnerability of this security mechanism. Previous studies have …
Generative Adversarial NetworkLarge Language ModelLLM JailbreakTalkFashion: Intelligent Virtual Try-On Assistant Based on Multimodal Large Language Model
Virtual try-on has made significant progress in recent years. This paper addresses how to achieve multifunctional virtual try-on guided solely by text instructions, including full outfit change and local editing. Previou…
Language ModelingLanguage ModellingLarge Language ModelMultimodal Large Language Model+1LeAD: The LLM Enhanced Planning System Converged with End-to-end Autonomous Driving
A principal barrier to large-scale deployment of urban autonomous driving systems lies in the prevalence of complex scenarios and edge cases. Existing systems fail to effectively interpret semantic information within tra…
Autonomous DrivingImitation LearningLanguage ModelingLanguage Modelling+1Automatic Synthesis of High-Quality Triplet Data for Composed Image Retrieval
As a challenging vision-language (VL) task, Composed Image Retrieval (CIR) aims to retrieve target images using multimodal (image+text) queries. Although many existing CIR methods have attained promising performance, the…
Image RetrievalLarge Language ModelRetrievalTripletVideo Event Reasoning and Prediction by Fusing World Knowledge from LLMs with Vision Foundation Models
Current video understanding models excel at recognizing "what" is happening but fall short in high-level cognitive tasks like causal reasoning and future prediction, a limitation rooted in their lack of commonsense world…
Future predictionLarge Language ModelVideo UnderstandingWorld Knowledge+1BlueLM-2.5-3B Technical Report
We present BlueLM-2.5-3B, a compact and unified dense Multimodal Large Language Model (MLLM) designed for efficient edge-device deployment, offering strong general-purpose and reasoning capabilities. To the best of our k…
Large Language ModelMultimodal Large Language Model