7 papers
Backtracking When It Strays: Mitigating Dual Exposure Biases in LLM Reasoning Distillation
Bing Wang, Shaotian Yan, Chen Shen +7
Large language models (LLMs) have achieved remarkable success in complex reasoning tasks via long chain-of-thought (CoT), yet their immense computational overhead hinders real-worl…
Are Rationales Necessary and Sufficient? Tuning LLMs for Explainable Misinformation Detection
Bing Wang, Rui Miao, Ximing Li +6
The rapid spread of misinformation on social media platforms has become a formidable challenge. To mitigate its proliferation, Misinformation Detection (MD) has emerged as a critic…
On the Step Length Confounding in LLM Reasoning Data Selection
Bing Wang, Rui Miao, Chen Shen +7
Large reasoning models have recently demonstrated strong performance on complex tasks that require long chain-of-thought reasoning, through supervised fine-tuning on large-scale an…
Where Did This Sentence Come From? Tracing Provenance in LLM Reasoning Distillation
Kaiyuan Liu, Shaotian Yan, Rui Miao +4
Reasoning distillation has attracted increasing attention. It typically leverages a large teacher model to generate reasoning paths, which are then used to fine-tune a student mode…
Distribution-Aligned Sequence Distillation for Superior Long-CoT Reasoning
Shaotian Yan, Kaiyuan Liu, Chen Shen +6
In this report, we introduce DASD-4B-Thinking, a lightweight yet highly capable, fully open-source reasoning model. It achieves SOTA performance among open-source models of compara…
GeoCAD: Local Geometry-Controllable CAD Generation with Large Language Models
Zhanwei Zhang, Kaiyuan Liu, Junjie Liu +5
Local geometry-controllable computer-aided design (CAD) generation aims to modify local parts of CAD models automatically, enhancing design efficiency. It also ensures that the sha…