4 citations · 10 across the 10 of their papers we have counts for
10 papers
daVinci-Dev: Agent-native Mid-training for Software Engineering
Ji Zeng, Dayuan Fu, Tiantian Mi +14
Recently, the frontier of Large Language Model (LLM) capabilities has shifted from single-turn code generation to agentic software engineering-a paradigm where models autonomously…
On The Fragility of Benchmark Contamination Detection in Reasoning Models
Han Wang, Haoyu Li, Brian Ko +1
Leaderboards for LRMs have turned evaluation into a competition, incentivizing developers to optimize directly on benchmark suites. A shortcut to achieving higher rankings is to in…
DecepChain: Inducing Deceptive Reasoning in Large Language Models
Wei Shen, Han Wang, Haoyu Li +1
Large Language Models (LLMs) have been demonstrating strong reasoning capability with their chain-of-thoughts (CoT), which are routinely used by humans to judge answer quality. Thi…
The Amazon Nova Family of Models: Technical Report and Model Card
Amazon AGI, Aaron Langford, Aayush Shah +783
We present Amazon Nova, a new generation of state-of-the-art foundation models that deliver frontier intelligence and industry-leading price performance. Amazon Nova Pro is a highl…
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time
Junyu Zhang, Runpei Dong, Han Wang +8
This paper presents AlphaOne (1), a universal framework for modulating reasoning progress in large reasoning models (LRMs) at test time. 1 first introduces moment, which…
Agentic Workflows for Economic Research: Design, Implementation, and Evaluation
Herbert Dawid, Philipp Harting, Hankui Wang +2
Large Language Models (LLMs) can now assist across the economic research lifecycle, yet general-purpose LLMs and agent systems give no assurance that their outputs meet the discipl…
TACOMORE: Exploring a replicable prompting protocol for LLM-assisted corpus analysis
Bingru Li, Han Wang, Nicholas Groom
As corpus linguistics continues to scale, researchers are facing a growing methodological bottleneck: while computational tools can easily count billions of words, the qualitative…
BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval
Hongjin Su, Howard Yen, Mengzhou Xia +12
Existing retrieval benchmarks primarily consist of information-seeking queries (e.g., aggregated questions from search engines) where keyword or semantic-based retrieval is usually…
MIMIR: A Streamlined Platform for Personalized Agent Tuning in Domain Expertise
Chunyuan Deng, Xiangru Tang, Yilun Zhao +5
Recently, large language models (LLMs) have evolved into interactive agents, proficient in planning, tool use, and task execution across a wide variety of tasks. However, without s…
MBGDT:Robust Mini-Batch Gradient Descent
Hanming Wang, Haozheng Luo, Yue Wang
In high dimensions, most machine learning method perform fragile even there are a little outliers. To address this, we hope to introduce a new method with the base learner, such as…