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20242026
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cs.CL2025

Enhancing Long Chain-of-Thought Reasoning through Multi-Path Plan Aggregation

Siheng Xiong, Ali Payani, Faramarz Fekri

Inference-time scaling enhances the reasoning ability of a language model (LM) by extending its chain-of-thought (CoT). However, existing approaches typically generate the entire r…

cs.CL2025

Deliberate Reasoning in Language Models as Structure-Aware Planning with an Accurate World Model

Siheng Xiong, Ali Payani, Yuan Yang +1

Enhancing the reasoning capabilities of language models (LMs) remains a key challenge, especially for tasks that require complex, multi-step decision-making where existing Chain-of…

cs.CL2025

MDBench: A Synthetic Multi-Document Reasoning Benchmark Generated with Knowledge Guidance

Joseph J. Peper, Wenzhao Qiu, Ali Payani +1

Natural language processing evaluation has made significant progress, largely driven by the proliferation of powerful large language mod-els (LLMs). New evaluation benchmarks are o…

cs.CL2024

Large Language Models Can Learn Temporal Reasoning

Siheng Xiong, Ali Payani, Ramana Kompella +1

While large language models (LLMs) have demonstrated remarkable reasoning capabilities, they are not without their flaws and inaccuracies. Recent studies have introduced various me…

cs.CL2024

Can LLMs Reason in the Wild with Programs?

Yuan Yang, Siheng Xiong, Ali Payani +2

Large Language Models (LLMs) have shown superior capability to solve reasoning problems with programs. While being a promising direction, most of such frameworks are trained and ev…