output_hidden_states: Optional[bool] = None, return_dict: Optional[bool] = None, ) -> Union[Tuple, SequenceClassifierOutputWithPast]: r""" labels (`torch.LongTensor` of shape `(batch_size,)`, *optional*): Labels for computing the sequence classification/regression loss. Indices...
For factual consistency of summaries, we use the FactCC metric, which is evaluated based on a binary classifier, and QuestEval, which is evaluated based on questions and answers. Denoted in the table as FC and QE, respectively. We also use ChatGPT-based G-Eval to evaluate the performance ...
The llm router essentially functions as a binary classifier, deciding whether to route a query to GPT-4 or Mixtral-8x7B based on the query text. Initially, we considered labeled data in the format (query, routing_label), where routing_label is 1 if the query should be routed to Mixtral...
34.Binary Classifier Optimization for Large Language Model Alignment 35.On the Limitations of Large Language Models (LLMs): False Attribution 36.Q-PEFT: Query-dependent Parameter Efficient Fine-tuning for Text Reranking with Large Language Models 37.Deciphering Political Entity Sentiment in News with...
To provide a more intuitive illustration of our definition of LLM hallucination, we present examples for each type of hallucination in Table 1, namely factuality hallucination and faithfulness hallucination. 然而,在LLMs时代,这些模型的多功能能力促进了它们在不同领域的广泛使用,突出了现有任务特定分类范式...
After a model is fine-tuned, it can be deployed on model hosting services such asAmazon SageMaker. The hosted model can then be used to generate candidate responses to various prompts. Through SageMaker Ground Truth, users can then provide feedback on which responses they prefer, resul...
Architecture-for-building-a-Chat-Assistant 🔗 LLM-CHAT-ASSISTANT-WITH-DYNAMIC-CONTEXT-BASED-ON-QUERY 🔗 Text Classifier using LLM 🔗 Multiclass sentiment Analysis 🔗 Text-Generation-Using-GROQ 🔗 DataAgents 🔗 PandasQuery_tabular_data 🔗 Exploratory_Data_Analysis_using_LLM...
The generator is fine-tuned on vulnerability fix data, with prompts enhanced by bug type annotations and semantically similar fixes, thereby improving the model’s ability to generate effective proposals. Improving repair capabilities through different strategies To improve the performance of LLMs on ...
SLM for reliable LLM generations SAPLMA (azaria2023internal) Using a BERT Small Language Model as a classifier to assess the truthfulness of statements accurately. SLM for reliable LLM generations Question Decomposer (wu2024divide) Distilled SLM decomposes complex questions to aid reasoning. SLM for ...
Therefore, an attempt was made to unify these into English prompts. This process can be seen in (i) of Fig. 5. Traditional Korean languages posed challenges for the latest LLMs, which could not understand them. Therefore, the GPT 3.5 is used, as it can easily translate word corpus into...