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Found 16 papers, 12 papers with code
Exploring Preference-Guided Diffusion Model for Cross-Domain Recommendation
To this end, we explore to utilize the explicit information injection capability of DMs for user preference integration and propose a Preference-Guided Diffusion Model for CDR to cold-start users, termed as DMCDR.
DEMO: Reframing Dialogue Interaction with Fine-grained Element Modeling
Despite the large volumes of dialogue-related studies, there is a lack of benchmark that encompasses comprehensive dialogue elements, which hinders precise modeling, generation and systematic evaluation.
IOPO: Empowering LLMs with Complex Instruction Following via Input-Output Preference Optimization
In the realm of large language models (LLMs), the ability of models to accurately follow instructions is paramount as more agents and applications leverage LLMs for construction, where the complexity of instructions are rapidly increasing.
On the Role of Attention Heads in Large Language Model Safety
In light of this, recent research on safety mechanisms has emerged, revealing that when safety representations or component are suppressed, the safety capability of LLMs are compromised.
The Imperative of Conversation Analysis in the Era of LLMs: A Survey of Tasks, Techniques, and Trends
In the era of large language models (LLMs), a vast amount of conversation logs will be accumulated thanks to the rapid development trend of language UI.
Revealing the Challenge of Detecting Character Knowledge Errors in LLM Role-Playing
Large language model (LLM) role-playing has gained widespread attention, where the authentic character knowledge is crucial for constructing realistic LLM role-playing agents.
LoginMEA: Local-to-Global Interaction Network for Multi-modal Entity Alignment
Other studies refine each uni-modal information with graph structures, but may introduce unnecessary relations in specific modalities.
IBMEA: Exploring Variational Information Bottleneck for Multi-modal Entity Alignment
To this end, we explore variational information bottleneck for multi-modal entity alignment (IBMEA), which emphasizes the alignment-relevant information and suppresses the alignment-irrelevant information in generating entity representations.
Ranked #1 on
Multi-modal Entity Alignment
on MMKG
Leave No Document Behind: Benchmarking Long-Context LLMs with Extended Multi-Doc QA
Long-context modeling capabilities have garnered widespread attention, leading to the emergence of Large Language Models (LLMs) with ultra-context windows.
How Alignment and Jailbreak Work: Explain LLM Safety through Intermediate Hidden States
Large language models (LLMs) rely on safety alignment to avoid responding to malicious user inputs.
Adaptive Data Augmentation for Aspect Sentiment Quad Prediction
Aspect sentiment quad prediction (ASQP) aims to predict the quad sentiment elements for a given sentence, which is a critical task in the field of aspect-based sentiment analysis.
Wider and Deeper LLM Networks are Fairer LLM Evaluators
Each perspective corresponds to the role of a specific LLM neuron in the first layer.
ID-MixGCL: Identity Mixup for Graph Contrastive Learning
Graph contrastive learning (GCL) has recently achieved substantial advancements.
A Cross-City Federated Transfer Learning Framework: A Case Study on Urban Region Profiling
To address the above challenging problems, we propose a novel Cross-city Federated Transfer Learning framework (CcFTL) to cope with the data insufficiency and privacy problems.
Improving Distantly-Supervised Named Entity Recognition with Self-Collaborative Denoising Learning
Distantly supervised named entity recognition (DS-NER) efficiently reduces labor costs but meanwhile intrinsically suffers from the label noise due to the strong assumption of distant supervision.
Exploring Periodicity and Interactivity in Multi-Interest Framework for Sequential Recommendation
Meanwhile, an ingenious graph is proposed to enhance the interactivity between items in user's behavior sequence, which can capture both global and local item features.
