#NeurIPS
98 related articles
·2 min
GLEE Competition: Build a Negotiation AI Agent and Sprint Toward NeurIPS 2026
The GLEE Competition challenges participants to build AI Agents that can bargain, negotiate, and persuade in real-time adversarial games, with a path to NeurIPS 2026 publication and $6,000 in prizes from Google and Salesforce.
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·3 min
NeurIPS Submissions Reveal New Trends in Research Collaboration in the AI Era
Analyzing a Reddit recruitment post to explore NeurIPS Workshop submission strategies, how AI coding tools reshape research productivity, and the opportunities and risks of global collaboration for young researchers.
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·3 min
The NeurIPS Review Dilemma: Why Do Reviewers Refuse to Raise Scores After Rebuttal Resolves Their Concerns?
Examining the structural contradiction in NeurIPS peer review: why reviewers acknowledge rebuttals resolve their concerns yet refuse to adjust scores, and its systemic impact on research.
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·2 min
GLEE Competition: A Detailed Guide to the NeurIPS 2026 Official Negotiation AI Challenge
NeurIPS 2026 GLEE Competition challenges AI agents to negotiate in real-time via natural language, covering bargaining, persuasion, and game strategies. Full guide on rules, approaches, and prizes.
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·2 min
Will NeurIPS Reviewers Actually Update Scores After Verbally Acknowledging Issues Are Resolved? An Experience-Based Analysis
Analysis of why NeurIPS reviewers often verbally acknowledge resolved concerns but don't update scores, plus strategies for authors during the discussion phase.
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·2 min
ICLR 2027 Deadline Before NeurIPS 2026 Decisions Sparks Controversy: The Deeper Conflicts in Top Conference Timelines
ICLR 2027's paper deadline falls 8 days before NeurIPS 2026 decisions, sparking debate over top conference timeline conflicts and their impact on researchers.
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·3 min
Low Initial Review Scores for NeurIPS 2026 Theory Papers? Community Discussion and In-Depth Analysis
NeurIPS 2026 theory papers are receiving low initial review scores. This article analyzes structural causes, scoring trends, and rebuttal strategies for theory researchers.
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·4 min
Testing a Research Automation Agent: Zero-Shot Reproduction of a NeurIPS Paper End-to-End
Testing research automation agent Klaus Goh: full reproduction of IBM's TTM time series paper at NeurIPS—from search to zero-shot inference, 2700+ predictions in 10 seconds, MSE 0.363 beating TimesFM.
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·3 min
EMNLP 2026 Acceptance Notification Countdown: Understanding the NLP Top Conference Review Process and Research Trends
EMNLP 2026 acceptance notifications are imminent. This article analyzes the NLP top conference peer review process, research trend shifts in the LLM era, and offers practical advice for researchers.
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·5 min
How Undergraduates Without Research Advisors Can Start Independent Research
How can undergraduates without advisors or labs conduct independent research? This guide covers paper reproduction, open resources, finding remote mentors, and publishing — a complete path for resource-limited students.
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·5 min
Reinforcement Learning for Obstacle Avoidance in CARLA: A Guide to Choosing Between DQN, PPO, and SAC
In-depth comparison of DQN, PPO, and SAC for obstacle avoidance in CARLA simulator, covering reward design strategies, simulation optimization, and practical guidance for autonomous driving RL researchers.
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·4 min
AI Algorithm Engineer Self-Study Roadmap: A Complete Plan from Zero to Landing Your First Offer
A detailed AI algorithm engineer self-study roadmap covering foundations, core algorithms, CV/NLP direction selection, and career transition strategies for landing offers.
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·2 min
Why Is NVIDIA Scrambling for Interns? A Deep Dive into the AI Talent War
NVIDIA's summer intern message reveals the AI chip giant's intense hunger for top talent. A deep dive into NVIDIA's talent strategy, the AI industry talent war, and what it means for young engineers.
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·3 min
RunTrace: A Local-First CLI Tool for ML Experiment Reproducibility
RunTrace is a lightweight open-source CLI tool that saves reproducibility context for ML experiments by recording Git status, Python environment, GPU info, and config files. Local-first with zero server dependencies.
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·3 min
Hugging Face Reproduces 2,200 ICML Papers: AI Research Reproducibility Crisis Fully Exposed
Hugging Face attempted to reproduce 2,200 ICML papers, exposing the machine learning reproducibility crisis. Analysis of code gaps, fragile dependencies, and compute barriers with paths forward.
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·3 min
Reproducing TS-JEPA Pitfalls: Where the Gap Between 0% and 74% Control Accuracy Lies
Deep analysis of the gap from 0% to 74.48% control accuracy when reproducing TS-JEPA, covering representation collapse, semantic actor training signals, and systematic debugging methodology.
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·2 min
everyone-can-use-english: An Open-Source AI English Learning Tool with 35K Stars
everyone-can-use-english is a 35K-star open-source English learning tool on GitHub, integrating Whisper ASR, TTS, and LLMs for intensive listening, shadowing, and AI conversation practice.
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·3 min
How to Plan an AI Security Career at 16? A Roadmap for Building Core Skills from Scratch
A 16-year-old wants to become an ML security engineer. This article outlines the AI security knowledge system, covering math foundations, ML, cybersecurity, and adversarial attack practice.
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·3 min
AI Agents Reproduce ICML 2026 Papers: 34% Verified, 23% Found Problematic
Hugging Face hosted an ICML 2026 Reproduction Hackathon where 1,200 participants used AI agents to verify 2,200 papers. Results: 34% covered, most reproducible, but ~23% had issues and 49 were nearly fully falsified.
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·3 min
CVPR Paper Dataset Never Released: A Crisis of Academic Integrity and Reproducibility
A CVPR 2026 paper's core dataset contribution was never released, with its GitHub repo remaining empty. We analyze the reproducibility crisis and how to file complaints.
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