22 citations · 38 across the 8 of their papers we have counts for
8 papers · 1 filter
DIVE: Unlocking Self-Improvement in Frozen Language Models Through Diversity-Driven Skill Evolution
Siheng Xiong, Ali Payani, Oguzhan Gungordu +1
Large language models (LLMs) cannot retain post-deployment experience without parameter updates. We introduce DIVE, a diversity-driven framework that enables frozen LLMs to improve…
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…
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…
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…
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…
TEILP: Time Prediction over Knowledge Graphs via Logical Reasoning
Siheng Xiong, Yuan Yang, Ali Payani +2
Conventional embedding-based models approach event time prediction in temporal knowledge graphs (TKGs) as a ranking problem. However, they often fall short in capturing essential t…