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Found 14 papers, 10 papers with code
Chain of Ideas: Revolutionizing Research Via Novel Idea Development with LLM Agents
Moreover, our CoI agent is budget-friendly, with a minimum cost of \$0. 50 to generate a candidate idea and its corresponding experimental design.
Can We Further Elicit Reasoning in LLMs? Critic-Guided Planning with Retrieval-Augmentation for Solving Challenging Tasks
We validate CR-Planner on challenging domain-knowledge-intensive and reasoning-heavy tasks, including competitive programming, theorem-driven math reasoning, and complex domain retrieval problems.
How Much are Large Language Models Contaminated? A Comprehensive Survey and the LLMSanitize Library
With the rise of Large Language Models (LLMs) in recent years, abundant new opportunities are emerging, but also new challenges, among which contamination is quickly becoming critical.
ParaICL: Towards Robust Parallel In-Context Learning
However, our preliminary experiments indicate that the effectiveness of ICL is limited by the length of the input context.
SeaLLMs -- Large Language Models for Southeast Asia
Despite the remarkable achievements of large language models (LLMs) in various tasks, there remains a linguistic bias that favors high-resource languages, such as English, often at the expense of low-resource and regional languages.
ChatGPT's One-year Anniversary: Are Open-Source Large Language Models Catching up?
Upon its release in late 2022, ChatGPT has brought a seismic shift in the entire landscape of AI, both in research and commerce.
Unlocking Temporal Question Answering for Large Language Models with Tailor-Made Reasoning Logic
The temporal aspect is a significant dimension of our reality.
Is GPT-4 a Good Data Analyst?
As large language models (LLMs) have demonstrated their powerful capabilities in plenty of domains and tasks, including context understanding, code generation, language generation, data storytelling, etc., many data analysts may raise concerns if their jobs will be replaced by artificial intelligence (AI).
Chain-of-Knowledge: Grounding Large Language Models via Dynamic Knowledge Adapting over Heterogeneous Sources
Specifically, CoK consists of three stages: reasoning preparation, dynamic knowledge adapting, and answer consolidation.
Verify-and-Edit: A Knowledge-Enhanced Chain-of-Thought Framework
As large language models (LLMs) have become the norm in NLP, demonstrating good performance in generation and reasoning tasks, one of its most fatal disadvantages is the lack of factual correctness.
Retrieving Multimodal Information for Augmented Generation: A Survey
As Large Language Models (LLMs) become popular, there emerged an important trend of using multimodality to augment the LLMs' generation ability, which enables LLMs to better interact with the world.
Evaluating Psychological Safety of Large Language Models
Despite being instruction fine-tuned with safety metrics to reduce toxicity, InstructGPT, GPT-3. 5, and GPT-4 still showed dark personality patterns; these models scored higher than self-supervised GPT-3 on the Machiavellianism and narcissism traits on SD-3.
Towards Robust Low-Resource Fine-Tuning with Multi-View Compressed Representations
Due to the huge amount of parameters, fine-tuning of pretrained language models (PLMs) is prone to overfitting in the low resource scenarios.
YEDDA: A Lightweight Collaborative Text Span Annotation Tool
And the annotation time can be further compressed by 16. 47\% through intelligent recommendation.
