Language Models (LMs) have shown impressive performance in various natural language
tasks. However, when it comes to natural language reasoning, LMs still face challenges …

While large language models (LLMs) have shown remarkable effectiveness in various NLP
tasks, they are still prone to issues such as hallucination, unfaithful reasoning, and toxicity. A …

State-of-the-art language models can exhibit impressive reasoning refinement capabilities
on math, science or coding tasks. However, recent work demonstrates that even the best …

The ability of Large Language Models (LLMs) to critique and refine their reasoning is crucial
for their application in evaluation, feedback provision, and self-improvement. This paper …

Recent advancements in large language models (LLMs) have propelled Artificial
Intelligence (AI) to new heights, enabling breakthroughs in various tasks such as writing …

Despite the high performances of large language models (LLMs) across numerous
benchmarks, recent research has unveiled their suffering from hallucinations and unfaithful …

Large language models (LLMs) have achieved remarkable performance in various
evaluation benchmarks. However, concerns are raised about potential data contamination in …

Large Language Models (LLMs) have exhibited remarkable reasoning capabilities and
become the foundation of language technologies. Inspired by the great success of code data …

Reasoning is a fundamental aspect of human intelligence that plays a crucial role in
activities such as problem solving, decision making, and critical thinking. In recent years …

Large language models (LLMs) have demonstrated remarkable performance across a wide
array of NLP tasks. However, their efficacy is undermined by undesired and inconsistent …