Papers with multi-dimensional control
ArgGenBench: Benchmarking the Complex Controlled Argument Generation Capability of Large Language Models (2026.acl-long)
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| Challenge: | Existing studies focus on limited control signals such as topic, stance, length, style, strategy, audience, and key aspects, failing to capture this complexity. |
| Approach: | They propose a benchmark that integrates multi-dimensional control into a single instruction to evaluate LLMs' ability to produce persuasive arguments. |
| Outcome: | The proposed benchmarks show that existing models fail to capture multifaceted argumentative control signals. |
seqBench: A Tunable Benchmark to Quantify Sequential Reasoning Limits of LLMs (2025.emnlp-main)
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| Challenge: | **seqBench** allows systematic variation of several key complexity dimensions. |
| Approach: | They introduce a parametrized benchmark for probing sequential reasoning limits in Large Language Models through precise, multi-dimensional control over several key complexity dimensions. |
| Outcome: | The framework allows systematic variation of logical depth, backtracking requirements and noise ratio on state-of-the-art LLMs. |