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Found 15 papers, 5 papers with code
Merging LoRAs like Playing LEGO: Pushing the Modularity of LoRA to Extremes Through Rank-Wise Clustering
The centroid of each cluster serves as a representative MSU, enabling the assembly of a merged LoRA with an adjusted rank of $k$.
IntOPE: Off-Policy Evaluation in the Presence of Interference
Off-Policy Evaluation (OPE) is employed to assess the potential impact of a hypothetical policy using logged contextual bandit feedback, which is crucial in areas such as personalized medicine and recommender systems, where online interactions are associated with significant risks and costs.
Causal Agent based on Large Language Model
In the tools module, the causal agent applies causal methods to align tabular data with natural language.
Leveraging Adaptive Implicit Representation Mapping for Ultra High-Resolution Image Segmentation
To address these limitations, we propose a novel approach that leverages the newly proposed Adaptive Implicit Representation Mapping (AIRM) for ultra-high-resolution Image Segmentation.
Sub-SA: Strengthen In-context Learning via Submodular Selective Annotation
In Sub-SA, we design a submodular function that facilitates effective subset selection for annotation and demonstrates the characteristics of monotonically and submodularity from the theoretical perspective.
Retrieval-Augmented Mixture of LoRA Experts for Uploadable Machine Learning
In UML, contributors use decentralized data to train specialized adapters, which are then uploaded to a central platform to improve LLMs.
PillarHist: A Quantization-aware Pillar Feature Encoder based on Height-aware Histogram
To address above issue, we first unveil the importance of different input information during PFE and identify the height dimension as a key factor in enhancing 3D detection performance.
Unbridled Icarus: A Survey of the Potential Perils of Image Inputs in Multimodal Large Language Model Security
Multimodal Large Language Models (MLLMs) demonstrate remarkable capabilities that increasingly influence various aspects of our daily lives, constantly defining the new boundary of Artificial General Intelligence (AGI).
LoraRetriever: Input-Aware LoRA Retrieval and Composition for Mixed Tasks in the Wild
Low-Rank Adaptation (LoRA) provides an effective yet efficient solution for fine-tuning large language models (LLM).
LiDAR-PTQ: Post-Training Quantization for Point Cloud 3D Object Detection
To our knowledge, for the very first time in lidar-based 3D detection tasks, the PTQ INT8 model's accuracy is almost the same as the FP32 model while enjoying $3\times$ inference speedup.
InfiAgent-DABench: Evaluating Agents on Data Analysis Tasks
In this paper, we introduce InfiAgent-DABench, the first benchmark specifically designed to evaluate LLM-based agents on data analysis tasks.
LogoStyleFool: Vitiating Video Recognition Systems via Logo Style Transfer
We separate the attack into three stages: style reference selection, reinforcement-learning-based logo style transfer, and perturbation optimization.
Modeling Transient Changes in Circadian Rhythms
The circadian clock can adapt itself to external cues, but the molecular mechanisms and regulatory networks governing circadian oscillations' transient adjustments are still largely unknown.
Few-Shot 3D Point Cloud Semantic Segmentation via Stratified Class-Specific Attention Based Transformer Network
While a few-shot learning method was proposed recently to address these two problems, it suffers from high computational complexity caused by graph construction and inability to learn fine-grained relationships among points due to the use of pooling operations.
Few-shot 3D Point Cloud Semantic Segmentation
Few-Shot Learning
+4
Learning Individual Treatment Effects under Heterogeneous Interference in Networks
In network data, due to interference, the outcome of a unit is influenced not only by its treatment (i. e., direct effects) but also by others' treatments (i. e., spillover effects).
