8 citations · 8 across the 9 of their papers we have counts for
9 papers
Sparse Layer Sharpness-Aware Minimization for Efficient Fine-Tuning
Yifei Cheng, Xianglin Yang, Guoxia Wang +5
Sharpness-aware minimization (SAM) seeks the minima with a flat loss landscape to improve the generalization performance in machine learning tasks, including fine-tuning. However,…
ProjDevBench: Benchmarking AI Coding Agents on End-to-End Project Development
Pengrui Lu, Shiqi Zhang, Yunzhong Hou +8
Recent coding agents can generate complete codebases from simple prompts, yet existing evaluations focus on issue-level bug fixing and lag behind end-to-end development. We introdu…
Who Deserves the Reward? SHARP: Shapley Credit-based Optimization for Multi-Agent System
Yanming Li, Xuelin Zhang, WenJie Lu +11
Integrating Large Language Models (LLMs) with external tools via multi-agent systems offers a promising new paradigm for decomposing and solving complex problems. However, training…
Why Your Deep Research Agent Fails? On Hallucination Evaluation in Full Research Trajectory
Yuhao Zhan, Tianyu Fan, Linxuan Huang +2
Diagnosing failure patterns in Deep Research Agents (DRAs) remains a critical challenge. Existing benchmarks predominantly rely on end-to-end evaluation, obscuring intermediate hal…
MME-CC: A Challenging Multi-Modal Evaluation Benchmark of Cognitive Capacity
Kaiyuan Zhang, Chenghao Yang, Zhoufutu Wen +19
As reasoning models scale rapidly, the essential role of multimodality in human cognition has come into sharp relief, driving a growing need to probe vision-centric cognitive behav…
Every Activation Boosted: Scaling General Reasoner to 1 Trillion Open Language Foundation
Ling Team, Ang Li, Ben Liu +138
We introduce Ling 2.0, a series reasoning-oriented language foundation built upon the principle that every activation boosts reasoning capability. Designed to scale from tens of bi…
Every Step Evolves: Scaling Reinforcement Learning for Trillion-Scale Thinking Model
Ling Team, Anqi Shen, Baihui Li +101
We present Ring-1T, the first open-source, state-of-the-art thinking model with a trillion-scale parameter. It features 1 trillion total parameters and activates approximately 50 b…
Justice or Prejudice? Quantifying Biases in LLM-as-a-Judge
Jiayi Ye, Yanbo Wang, Yue Huang +9
LLM-as-a-Judge has been widely utilized as an evaluation method in various benchmarks and served as supervised rewards in model training. However, despite their excellence in many…
Investigating Decoder-only Large Language Models for Speech-to-text Translation
Chao-Wei Huang, Hui Lu, Hongyu Gong +4
Large language models (LLMs), known for their exceptional reasoning capabilities, generalizability, and fluency across diverse domains, present a promising avenue for enhancing spe…