2 citations · 5 across the 19 of their papers we have counts for
24 papers
Search for High-Energy Neutrinos from Infrared Flares
R. Abbasi, M. Ackermann, J. Adams +415
IceCube has detected a diffuse flux of high-energy astrophysical neutrinos. While its astrophysical origin is unknown, a significant neutrino emission has been observed from the ga…
Planck-Scale Constraints on Quantum Gravity-Induced Neutrino Decoherence with IceCube
R. Abbasi, M. Ackermann, J. Adams +415
Many quantum gravity theories predict spacetime fluctuations at the Planck scale. Neutrinos, which interact only via the weak force and gravity, propagate over long distances witho…
Opera: A Verbal Critic Framework for Long-horizon Coding Agents
Kai Mei, Zhiyuan Hu, Yutong Dai +7
Long-horizon coding agents need timely corrections, yet feedback can be ineffective or even harmful when it misjudges ongoing work or fails to address the underlying problem. Exist…
Time-Integrated Searches for Sub-TeV Neutrino Sources with IceCube-DeepCore
R. Abbasi, M. Ackermann, J. Adams +418
We have developed techniques for a competitive sub-TeV time-integrated neutrino search and applied it to 11.1 years of IceCube-DeepCore data. The DeepCore subarray lowers the sensi…
IceCube neutrino point-source searches in the direction of the KM3NeT ultra-high-energy event
R. Abbasi, M. Ackermann, J. Adams +416
While still under construction, the KM3NeT Astroparticle Research with Cosmics in the Abyss (ARCA) detector recorded a 200 PeV neutrino on February 13th, 2023. This event is…
Search for Neutrinos from Tidal Disruption Events with IceCube
R. Abbasi, M. Ackermann, J. Adams +417
Tidal disruption events (TDEs) are theorized to produce high-energy neutrinos through photohadronic interactions between accelerated protons and multi-wavelength photons in the acc…
Dr. Claw: An AI Scientist Workspace for Vibe Research
Dingjie Song, Hanrong Zhang, Dawei Liu +10
Command-line coding agents (e.g., Claude Code, Gemini CLI) can already read and write files and sustain long sessions, yet end-to-end research still fragments across chat tools, ID…
Searching for Extra Dimensions and Copies of the Standard Model with IceCube
R. Abbasi, M. Ackermann, J. Adams +418
The hierarchy problem remains an open question in particle physics. A number of theories that address this problem lower the fundamental scale of gravity, resulting in observable c…
Astrophysical Sensitivity Projections for the IceCube Upgrade
R. Abbasi, M. Ackermann, J. Adams +417
Embedded in the South Pole's glacial ice, IceCube detects neutrino-induced Cherenkov light using an array of digital optical modules equipped with single photomultiplier tubes (PMT…
WavePID: Low-energy flavor identification using single-PMT time series in IceCube
The IceCube Collaboration, R. Abbasi, M. Ackermann +417
The IceCube Neutrino Observatory, a cubic-kilometer detector at the South Pole, identifies neutrino flavor through event morphology. Sparse photon detection makes this classificati…
Estimating the sensitivity of the IceCube Upgrade to probe the interior of the Earth using atmospheric neutrino oscillations
The IceCube Collaboration, R. Abbasi, M. Ackermann +421
The IceCube Upgrade is a densely instrumented central region of the IceCube Neutrino Observatory, deployed during the 2025-26 polar season. It will reduce the detector's energy thr…
High-energy neutrino emission from the Milky Way
R. Abbasi, M. Ackermann, J. Adams +420
The Milky Way hosts astrophysical objects that accelerate cosmic rays to energies beyond the reach of terrestrial particle accelerators. It remains a longstanding goal to locate th…
High-Energy Neutrino Tomography of the Earth's Interior with IceCube
The IceCube Collaboration, R. Abbasi, M. Ackermann +417
The Earth's interior reflects its geological evolution, from accretion to present-day dynamics. Its structure drives the geodynamo in the outer core, generating the magnetic field…
OpenSkill: Open-World Self-Evolution for LLM Agents
Zhiling Yan, Dingjie Song, Hanrong Zhang +8
Self-evolving agents requires adaptation after deployment, but existing approaches assume a usable learning loop, such as curated skills, successful trajectories, or verifier signa…
AutoResearch AI: Towards AI-Powered Research Automation for Scientific Discovery
Guiyao Tie, Jiawen Shi, Dingjie Song +20
Scientific research is being reshaped by AI systems that move beyond isolated assistance toward longer-horizon workflows spanning literature grounding, hypothesis generation, exper…
IceCube Second Track Data Release IceTracks-DR2: Data from 2008-2022 for Neutrino Source Searches
R. Abbasi, M. Ackermann, J. Adams +412
We present IceCube's latest release of muon track data for neutrino point-source searches, extending the previously published 10-year dataset to cover 14 years of observations (Apr…
Towards a Medical AI Scientist
Hongtao Wu, Boyun Zheng, Dingjie Song +5
Autonomous systems that generate scientific hypotheses, conduct experiments, and draft manuscripts have recently emerged as a promising paradigm for accelerating discovery. However…
Can MLLMs Read Students' Minds? Unpacking Multimodal Error Analysis in Handwritten Math
Dingjie Song, Tianlong Xu, Yi-Fan Zhang +6
Assessing student handwritten scratchwork is crucial for personalized educational feedback but presents unique challenges due to diverse handwriting, complex layouts, and varied pr…
LiveMedBench: A Contamination-Free Medical Benchmark for LLMs with Automated Rubric Evaluation
Zhiling Yan, Dingjie Song, Zhe Fang +4
The deployment of Large Language Models (LLMs) in high-stakes clinical settings demands rigorous and reliable evaluation. However, existing medical benchmarks remain static, suffer…
SAMed-2: Selective Memory Enhanced Medical Segment Anything Model
Zhiling Yan, Sifan Song, Dingjie Song +11
Recent "segment anything" efforts show promise by learning from large-scale data, but adapting such models directly to medical images remains challenging due to the complexity of m…
Agentic Robot: A Brain-Inspired Framework for Vision-Language-Action Models in Embodied Agents
Zhejian Yang, Yongchao Chen, Xueyang Zhou +8
Long-horizon robotic manipulation poses significant challenges for autonomous systems, requiring extended reasoning, precise execution, and robust error recovery across complex seq…
Aligning Multimodal LLM with Human Preference: A Survey
Tao Yu, Yi-Fan Zhang, Chaoyou Fu +14
Large language models (LLMs) can handle a wide variety of general tasks with simple prompts, without the need for task-specific training. Multimodal Large Language Models (MLLMs),…
A Survey on Post-training of Large Language Models
Guiyao Tie, Zeli Zhao, Dingjie Song +23
The emergence of Large Language Models (LLMs) has fundamentally transformed natural language processing, making them indispensable across domains ranging from conversational system…
From Correctness to Comprehension: AI Agents for Personalized Error Diagnosis in Education
Yi-Fan Zhang, Hang Li, Dingjie Song +3
Large Language Models (LLMs), such as GPT-4, have demonstrated impressive mathematical reasoning capabilities, achieving near-perfect performance on benchmarks like GSM8K. However,…