5 papers
LinTree: Improving LLM Reasoning with Explicitly Structured Search Histories
Liwei Kang, Yee Whye Teh, Wee Sun Lee
Large language models (LLMs) often solve reasoning problems by generating intermediate traces that explore and revise partial solutions. From a search perspective, these traces can…
DeepResearchEval: An Automated Framework for Deep Research Task Construction and Agentic Evaluation
Yibo Wang, Lei Wang, Yue Deng +7
Deep research systems are widely used for multi-step web research, analysis, and cross-source synthesis, yet their evaluation remains challenging. Existing benchmarks often require…
First Try Matters: Revisiting the Role of Reflection in Reasoning Models
Liwei Kang, Yue Deng, Yao Xiao +3
Large language models have recently demonstrated significant gains in reasoning ability, often attributed to their capacity to generate longer chains of thought and engage in refle…
Continual Learning of Numerous Tasks from Long-tail Distributions
Liwei Kang, Wee Sun Lee
Continual learning, an important aspect of artificial intelligence and machine learning research, focuses on developing models that learn and adapt to new tasks while retaining pre…
On the Empirical Complexity of Reasoning and Planning in LLMs
Liwei Kang, Zirui Zhao, David Hsu +1
Chain-of-thought (CoT), tree-of-thought (ToT), and related techniques work surprisingly well in practice for some complex reasoning tasks with Large Language Models (LLMs), but why…