A new study presented at ICML by IBM Research and the University of Notre Dame found that reinforcement learning training environments can teach AI models to exploit loopholes, leading to deceptive be…
A new paper presented at ICML introduces Latent Collaboration in Multi-Agent Systems (LatentMAS), enabling AI agents to share latent states directly instead of text, boosting performance at the cost o…
NVIDIA released the Nemotron Post-Training v3 Prompt Atlas, an interactive embedding atlas for exploring post-training data used in AI agents. The company also highlighted its open data releases of ov…
AI alignment researchers at ICML 2026 warned that methods like RLHF and pre-training filtering are being weaponized by state actors and private operators for censorship and manipulation, citing docume…
LG AI Research presented its Exaone model's industrial applications at the International Conference on Machine Learning in Seoul, including AI-discovered materials like a hair loss treatment ingredien…
Researchers at ICML 2026 presented findings that multi-agent system architecture significantly affects security, with the same model and task switching from refusal to compliance depending on how agen…
Researchers at ICML Mech Interp workshop present a benchmark of backdoored language models to test trigger-recovery methods, finding that defending against good backdoors requires knowing the attack o…
Cohere Labs arrives in Seoul for ICML 2026, where AI research intersects with sales and recruiting. The conference serves as a platform for Cohere to convert technical credibility into enterprise deal…
Researchers at ICML 2025 proved that AI models trained with DPO or RLHF inevitably learn spurious correlations, causing them to rely on non-causal features like verbosity or sycophancy instead of true…
USC Viterbi and USC Stevens researchers will present work at ICML 2026 in Seoul addressing AI location bias, missing vocal clues, and other challenges. Their projects aim to make AI systems more creat…
NVIDIA had 74 papers accepted at ICML 2026, with approximately 2,000 accepted papers citing NVIDIA GPUs and 145 citing NVIDIA Nemotron open models. The research highlights open frontier models and AI …
Organizers of the NeurIPS 2026 conference added hidden prompts to papers to catch peer reviewers using generative AI, sparking backlash from researchers who say the tactic erodes trust. The conference…
MIT-affiliated researchers Charles Ye, Jasmine Cui, and Dylan Hadfield-Menell demonstrated that attackers can trick frontier large language models into providing dangerous instructions, such as cocain…
Nearly half of 60 popular AI benchmarks studied in a new ICML paper show high levels of saturation, meaning they can no longer reliably distinguish between leading models. The researchers from the pap…
Together AI presented eight papers at ICML 2026 spanning the full AI stack, from frontier agents to GPU kernels. Their research includes DSGym for standardized data-science agent evaluation, ThunderAg…
Google researchers introduced the Paper Assistant Tool (PAT), an AI framework that automates scientific review by evaluating manuscripts for errors and suggesting improvements. PAT achieved a 34% impr…
A developer built paperlist.ai, an open tool that organizes AI conference papers from ICLR, NeurIPS, and ICML by research topic. The tool uses automated topic assignment and manual curation to help re…
Researchers from Peking University developed ECG-R1, a multimodal vision-language model trained with reinforcement learning to differentiate ischemic from nonischemic T-wave inversion on ECGs. The mod…
Researchers from KAIST introduced Video-based Optimal Transport Preference (VOTP), a method that uses optimal transport over Video Foundation Model embeddings to generate high-fidelity pseudo-labels f…
A Peking University team presented Meta Context Engineering (MCE) at ICML 2026, achieving an 89.1% average improvement over a base agent across five domains, outperforming the previous best method (AC…