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Found 13 papers, 6 papers with code
Sibyl: Simple yet Effective Agent Framework for Complex Real-world Reasoning
To address these limitations, we introduce Sibyl, a simple yet powerful LLM-based agent framework designed to tackle complex reasoning tasks by efficiently leveraging a minimal set of tools.
Planning with Large Language Models for Conversational Agents
To bridge this gap, we propose a new framework for planning-based conversational agents (PCA) powered by large language models (LLMs), which only requires humans to define tasks and goals for the LLMs.
DART: Deep Adversarial Automated Red Teaming for LLM Safety
To mitigate this issue, we propose a Deep Adversarial Automated Red Teaming (DART) framework in which the Red LLM and Target LLM are deeply and dynamically interacting with each other in an iterative manner.
IRCAN: Mitigating Knowledge Conflicts in LLM Generation via Identifying and Reweighting Context-Aware Neurons
To mitigate such knowledge conflicts, we propose a novel framework, IRCAN (Identifying and Reweighting Context-Aware Neurons) to capitalize on neurons that are crucial in processing contextual cues.
GIEBench: Towards Holistic Evaluation of Group Identity-based Empathy for Large Language Models
As large language models (LLMs) continue to develop and gain widespread application, the ability of LLMs to exhibit empathy towards diverse group identities and understand their perspectives is increasingly recognized as critical.
Benchmarks Underestimate the Readiness of Multi-lingual Dialogue Agents
However, after manual evaluation of the validation set, we find that by correcting gold label errors and improving dataset annotation schema, GPT-4 with our prompts can achieve (1) 89. 6%-96. 8% accuracy in DST, and (2) more than 99% correct response generation across different languages.
ChatMusician: Understanding and Generating Music Intrinsically with LLM
It is based on continual pre-training and finetuning LLaMA2 on a text-compatible music representation, ABC notation, and the music is treated as a second language.
OpenCodeInterpreter: Integrating Code Generation with Execution and Refinement
However, open-source models often lack the execution capabilities and iterative refinement of advanced systems like the GPT-4 Code Interpreter.
RoleEval: A Bilingual Role Evaluation Benchmark for Large Language Models
We expect that RoleEval would highlight the significance of assessing role knowledge for large language models across various languages and cultural settings.
Large Language Model Alignment: A Survey
We also envision bridging the gap between the AI alignment research community and the researchers engrossed in the capability exploration of LLMs for both capable and safe LLMs.
X-RiSAWOZ: High-Quality End-to-End Multilingual Dialogue Datasets and Few-shot Agents
We create a new multilingual benchmark, X-RiSAWOZ, by translating the Chinese RiSAWOZ to 4 languages: English, French, Hindi, Korean; and a code-mixed English-Hindi language.
GEMv2: Multilingual NLG Benchmarking in a Single Line of Code
This problem is especially pertinent in natural language generation which requires ever-improving suites of datasets, metrics, and human evaluation to make definitive claims.
A Hybrid Task-Oriented Dialog System with Domain and Task Adaptive Pretraining
This paper describes our submission for the End-to-end Multi-domain Task Completion Dialog shared task at the 9th Dialog System Technology Challenge (DSTC-9).
