Search Results for author:
Found 11 papers, 9 papers with code
Robust Few-Shot Ensemble Learning with Focal Diversity-Based Pruning
This paper presents FusionShot, a focal diversity optimized few-shot ensemble learning approach for boosting the robustness and generalization performance of pre-trained few-shot models.
A Survey on Large Language Model-Based Game Agents
The development of game agents holds a critical role in advancing towards Artificial General Intelligence (AGI).
PokeLLMon: A Human-Parity Agent for Pokemon Battles with Large Language Models
We introduce PokeLLMon, the first LLM-embodied agent that achieves human-parity performance in tactical battle games, as demonstrated in Pokemon battles.
Vaccine: Perturbation-aware Alignment for Large Language Model
The new paradigm of finetuning-as-a-service introduces a new attack surface for Large Language Models (LLMs): a few harmful data uploaded by users can easily trick the finetuning to produce an alignment-broken model.
Large Language Model-Powered Smart Contract Vulnerability Detection: New Perspectives
The goal of auditor is to yield a broad spectrum of vulnerabilities with the hope of encompassing the correct answer, whereas the goal of critic that evaluates the validity of identified vulnerabilities is to minimize the number of false positives.
BERT4ETH: A Pre-trained Transformer for Ethereum Fraud Detection
As various forms of fraud proliferate on Ethereum, it is imperative to safeguard against these malicious activities to protect susceptible users from being victimized.
Adaptive Deep Neural Network Inference Optimization with EENet
Instead of having every sample go through all DNN layers during prediction, EENet learns an early exit scheduler, which can intelligently terminate the inference earlier for certain predictions, which the model has high confidence of early exit.
Deep Intention-Aware Network for Click-Through Rate Prediction
We identify that the key to TIRA is to extract customers' personalized entering intention and weigh the impact of triggers based on this intention.
Sequence-Based Target Coin Prediction for Cryptocurrency Pump-and-Dump
With the proliferation of pump-and-dump schemes (P&Ds) in the cryptocurrency market, it becomes imperative to detect such fraudulent activities in advance to alert potentially susceptible investors.
GIFT: Graph-guIded Feature Transfer for Cold-Start Video Click-Through Rate Prediction
Specifically, we establish a heterogeneous graph that contains physical and semantic linkages to guide the feature transfer process from warmed-up video to cold-start videos.
From Known to Unknown: Knowledge-guided Transformer for Time-Series Sales Forecasting in Alibaba
Except for introducing future knowledge for prediction, we propose Aliformer based on the bidirectional Transformer, which can utilize the historical information, current factor, and future knowledge to predict future sales.
