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ArXiv Domain 2025-07-14
数据来源:ArXiv Domain
LLM Domain Papers1. One Token to Fool LLM-as-a-JudgeGenerative reward models (also known as LLMs-as-judges), which use large language models (LLMs) to evaluate answer quality, are increasingly adopted in reinforcement learning with verifiable rewards (RLVR). They are often preferred over rigid rule-based metrics, especially for complex reasoning tasks involving free-form outputs. In this paradigm, an LLM is typically prompted to compare a candidate answer against a ground-tru ...
ArXiv Domain 2025-07-15
数据来源:ArXiv Domain
LLM Domain Papers1. CodeJudgeBench: Benchmarking LLM-as-a-Judge for Coding TasksLarge Language Models (LLMs) have significantly advanced the state-of-the-art in various coding tasks. Beyond directly answering user queries, LLMs can also serve as judges, assessing and comparing the quality of responses generated by other models. Such an evaluation capability is crucial both for benchmarking different LLMs and for improving response quality through response ranking. However, de ...
ArXiv Domain 2025-07-16
数据来源:ArXiv Domain
LLM Domain Papers1. CodeJudgeBench: Benchmarking LLM-as-a-Judge for Coding TasksLarge Language Models (LLMs) have significantly advanced the state-of-the-art in various coding tasks. Beyond directly answering user queries, LLMs can also serve as judges, assessing and comparing the quality of responses generated by other models. Such an evaluation capability is crucial both for benchmarking different LLMs and for improving response quality through response ranking. However, de ...
ArXiv Domain 2025-07-17
数据来源:ArXiv Domain
LLM Domain Papers1. Web-Browsing LLMs Can Access Social Media Profiles and Infer User DemographicsLarge language models (LLMs) have traditionally relied on static training data, limiting their knowledge to fixed snapshots. Recent advancements, however, have equipped LLMs with web browsing capabilities, enabling real time information retrieval and multi step reasoning over live web content. While prior studies have demonstrated LLMs ability to access and analyze websites, thei ...
ArXiv Domain 2025-07-18
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LLM Domain Papers1. Comparing Apples to Oranges: A Dataset & Analysis of LLM Humour Understanding from Traditional Puns to Topical JokesHumour, as a complex language form, is derived from myriad aspects of life, whilst existing work on computational humour has focussed almost exclusively on short pun-based jokes. In this work, we investigate whether the ability of Large Language Models (LLMs) to explain humour depends on the particular humour form. We compare models on si ...
ArXiv Domain 2025-09-26
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LLM Domain Papers1. From Prediction to Understanding: Will AI Foundation Models Transform Brain Science?Generative pretraining (the “GPT” in ChatGPT) enables language models to learn from vast amounts of internet text without human supervision. This approach has driven breakthroughs across AI by allowing deep neural networks to learn from massive, unstructured datasets. We use the term foundation models to refer to large pretrained systems that can be adapted to a wide range ...
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