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Found 29 papers, 9 papers with code
CoLV: A Collaborative Latent Variable Model for Knowledge-Grounded Dialogue Generation
Knowledge-grounded dialogue generation has achieved promising performance with the engagement of external knowledge sources.
DGFamba: Learning Flow Factorized State Space for Visual Domain Generalization
By aligning these probability paths in the latent space, the state embeddings are able to represent the same content distribution regardless of the style differences.
Learning Fine-grained Domain Generalization via Hyperbolic State Space Hallucination
Then, the pre- and post- style hallucinate state embeddings are projected into the hyperbolic manifold.
NightAdapter: Learning a Frequency Adapter for Generalizable Night-time Scene Segmentation
Night-time scene segmentation is a critical yet challenging task in the real-world applications, primarily due to the complicated lighting conditions.
Cut the Deadwood Out: Post-Training Model Purification with Selective Module Substitution
The success of DNNs often depends on training with large-scale datasets, but building such datasets is both expensive and challenging.
Scalable Frame-based Construction of Sociocultural NormBases for Socially-Aware Dialogues
Our empirical results show: (i) the quality of the SCNs derived from synthetic data is comparable to that from real dialogues annotated with gold frames, and (ii) the quality of the SCNs extracted from real data, annotated with either silver (predicted) or gold frames, surpasses that without the frame annotations.
Learning Spectral-Decomposed Tokens for Domain Generalized Semantic Segmentation
In this paper, we present a novel Spectral-dEcomposed Token (SET) learning framework to advance the frontier.
BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions
In addition, using multiple tools to solve a task needs compositional reasoning by accurately understanding complex instructions.
Ranked #1 on
Code Generation
on BigCodeBench-Instruct
SCAR: Efficient Instruction-Tuning for Large Language Models via Style Consistency-Aware Response Ranking
Recent studies emphasize that manually ensuring a consistent response style and maintaining high data quality in training sets can significantly improve the performance of fine-tuned Large Language Models (LLMs) while reducing the number of training examples needed.
IMO: Greedy Layer-Wise Sparse Representation Learning for Out-of-Distribution Text Classification with Pre-trained Models
Machine learning models have made incredible progress, but they still struggle when applied to examples from unseen domains.
GOOD: Towards Domain Generalized Orientated Object Detection
In this paper, we propose the task of domain generalized oriented object detection, which intends to explore the generalization of oriented object detectors on arbitrary unseen target domains.
RENOVI: A Benchmark Towards Remediating Norm Violations in Socio-Cultural Conversations
While collecting sufficient human-authored data is costly, synthetic conversations provide suitable amounts of data to help mitigate the scarcity of training data, as well as the chance to assess the alignment between LLMs and humans in the awareness of social norms.
Let's Negotiate! A Survey of Negotiation Dialogue Systems
Negotiation is a crucial ability in human communication.
SADAS: A Dialogue Assistant System Towards Remediating Norm Violations in Bilingual Socio-Cultural Conversations
We have released our code and software at:~\url{https://github. com/AnonymousEACLDemo/SADAS}.
Cross-Level Multi-Instance Distillation for Self-Supervised Fine-Grained Visual Categorization
To comprehensively learn the relation between informative patches and fine-grained semantics, the multi-instance knowledge distillation is implemented on both the region/image crop pairs from the teacher and student net, and the region-image crops inside the teacher / student net, which we term as intra-level multi-instance distillation and inter-level multi-instance distillation.
Fine-Grained Visual Categorization
Knowledge Distillation
+2
Natural Language Processing for Dialects of a Language: A Survey
Motivated by the performance degradation of NLP models for dialectal datasets and its implications for the equity of language technologies, we survey past research in NLP for dialects in terms of datasets, and approaches.
Pairwise GUI Dataset Construction Between Android Phones and Tablets
There are currently several publicly accessible GUI page datasets for phones, but none for pairwise GUIs between phones and tablets.
G3Detector: General GPT-Generated Text Detector
The burgeoning progress in the field of Large Language Models (LLMs) heralds significant benefits due to their unparalleled capacities.
Turning Flowchart into Dialog: Augmenting Flowchart-grounded Troubleshooting Dialogs via Synthetic Data Generation
Flowchart-grounded troubleshooting dialogue (FTD) systems, which follow the instructions of a flowchart to diagnose users' problems in specific domains (e. g., vehicle, laptop), have been gaining research interest in recent years.
SocialDial: A Benchmark for Socially-Aware Dialogue Systems
To the best of our knowledge, SocialDial is the first socially-aware dialogue dataset that covers multiple social factors and has fine-grained labels.
Cultural Vocal Bursts Intensity Prediction
Synthetic Data Generation
Towards Zero-Shot Personalized Table-to-Text Generation with Contrastive Persona Distillation
Specifically, tabular data and persona information are firstly represented as latent variables separately.
Let's Negotiate! A Survey of Negotiation Dialogue Systems
Negotiation is one of the crucial abilities in human communication, and there has been a resurgent research interest in negotiation dialogue systems recently, which goal is to empower intelligent agents with such ability that can efficiently help humans resolve conflicts or reach beneficial agreements.
Identifying Untrustworthy Samples: Data Filtering for Open-domain Dialogues with Bayesian Optimization
The training method updates parameters of a trained NCMs on two small sets with newly maintained and removed samples, respectively.
Text is NOT Enough: Integrating Visual Impressions into Open-domain Dialogue Generation
Specifically, we obtain a group of images (PVIs) for each post based on a pre-trained word-image mapping model.
Augmenting Knowledge-grounded Conversations with Sequential Knowledge Transition
In particular, a sequential knowledge transition model equipped with a pre-trained knowledge-aware response generator (SKT-KG) formulates the high-level knowledge transition and fully utilizes the limited knowledge data.
Probing Product Description Generation via Posterior Distillation
To tackle this problem, we propose an adaptive posterior network based on Transformer architecture that can utilize user-cared information from customer reviews.
Learning to Select Context in a Hierarchical and Global Perspective for Open-domain Dialogue Generation
Open-domain multi-turn conversations mainly have three features, which are hierarchical semantic structure, redundant information, and long-term dependency.
User-Inspired Posterior Network for Recommendation Reason Generation
A simple and effective way is to extract keywords directly from the knowledge-base of products, i. e., attributes or title, as the recommendation reason.
Modeling Semantic Relationship in Multi-turn Conversations with Hierarchical Latent Variables
Multi-turn conversations consist of complex semantic structures, and it is still a challenge to generate coherent and diverse responses given previous utterances.
