The field of large language models (LLMs) is rapidly advancing, with a focus on evaluating their capabilities for complex tasks such as reasoning, argumentation, and decision-making. Recent developments have led to the creation of various benchmarks and evaluation frameworks, aiming to assess the performance of LLMs in real-world scenarios. These benchmarks cover a range of tasks, including scientific reasoning, critical thinking, and intent understanding, highlighting the need for more nuanced and comprehensive evaluation methods. Notable papers in this area include ELAIPBench, which evaluates LLMs' comprehension of artificial intelligence research papers, and MorphoBench, a benchmark that adaptively modifies its difficulty based on the reasoning abilities of advanced models. Overall, the field is moving towards more rigorous and realistic evaluations of LLMs, with a focus on their ability to perform complex tasks and generalize across different domains.
Evaluating Large Language Models for Complex Tasks
Sources
ASC analyzer: A Python package for measuring argument structure construction usage in English texts
Rethinking RL Evaluation: Can Benchmarks Truly Reveal Failures of RL Methods?
ELAIPBench: A Benchmark for Expert-Level Artificial Intelligence Paper Understanding
Rethinking LLM Evaluation: Can We Evaluate LLMs with 200x Less Data?
FML-bench: A Benchmark for Automatic ML Research Agents Highlighting the Importance of Exploration Breadth
PaperArena: An Evaluation Benchmark for Tool-Augmented Agentic Reasoning on Scientific Literature
ACADREASON: Exploring the Limits of Reasoning Models with Academic Research Problems
CGBench: Benchmarking Language Model Scientific Reasoning for Clinical Genetics Research
PricingLogic: Evaluating LLMs Reasoning on Complex Tourism Pricing Tasks
Toward LLM-Supported Automated Assessment of Critical Thinking Subskills
ConsintBench: Evaluating Language Models on Real-World Consumer Intent Understanding
Selective Adversarial Attacks on LLM Benchmarks
International AI Safety Report 2025: First Key Update: Capabilities and Risk Implications
MorphoBench: A Benchmark with Difficulty Adaptive to Model Reasoning