🎉Very excited to share that Jinesis Lab at the University of Toronto has 10 papers accepted at EMNLP 2026 — 5 at the main conference, 4 at Findings, and 1 at the Demo track! Our work this cycle spans interpretability, AI safety, computer vision, and multi-agent systems: 📌Main Conference: • Tracing Multilingual Representations in LLMs with Cross-Layer Transcoders — arxiv.org/abs/2511.10840 • PruneGround: Plug-and-play Spatial Pruning for 3D Visual Grounding — arxiv.org/abs/2606.31148 • How Do Linear Probes Emerge? A Circuit-Tracing Framework with Concept-Targeted Attribution • Computation Graph Recovery from Chain-of-Thought — openreview.net/pdf?id=OHES5c… • Preserving Historical Truth: Detecting Historical Revisionism in Large Language Models — arxiv.org/abs/2602.17433 📌Findings: • Evaluating Second-Order Bias of LLMs Through Epistemic Entitlement — arxiv.org/abs/2606.17506 • How Does Alignment Tuning Shape Representations of Sycophancy and Related Cue-Induced Biases in LLMs? — arxiv.org/pdf/2607.18114 • Simulating Democratic Deliberation: Representing Pluralistic Preferences through Electoral Systems in Multi-Agent LLMs • Fluid Representations in Reasoning Models — arxiv.org/abs/2602.04843 📌Demo Track: • CLT-Forge: A Scalable Library for Cross-Layer Transcoders and Attribution Graphs Huge congratulations to all the authors and collaborators across the lab and our partner institutions. @AHarrasse1906, @flodraye, @psyonp, @ZhijingJin, @bschoelkopf, Duc Cao Dinh, @leduckhai, Chris Ngo, @TerryJCZhang, @vedantpalit1008, @RoderickWu4, Aydin Javadov, @francescortu, @JoeunYk05, @albecazzaniga, @radamihalcea, @RamaravindM, Raiyan Ahmed, Shion Guha, Syed Ishtiaque Ahmed, Prakhar Gupta, @_rfaulk, @SSzufa, Daniel Hoyer, Roland Bouffanais, @jzl86, Dmitrii Kharlapenko, @iarthsingh, @alesstolfo, @ArthurConmy, @mrinmayasachan, @TonyWu1105, @Jiarui_Liu_, Chih-Hao Hsu. #EMNLP2026 #NLP #Interpretability #AISafety #MachineLearning

🌟 We’d love to welcome you as a reviewer for the 2nd Trustworthy AI4GOOD Workshop at #NeurIPS2026 in Paris! 🇫🇷 Following the success of our first edition at #ICML2026, this workshop will once again bring together researchers and practitioners working to ensure that advances in AI are not only powerful, but also trustworthy, responsible, and genuinely beneficial to society. Each reviewer will be assigned no more than 3 papers through OpenReview, with no paper bidding or rebuttal phase. 🗓️ Review period: September 2026 ⏰ Review deadline: September 22, 2026, AOE Please make sure your OpenReview profile is up to date before registering. Join us as a reviewer: forms.gle/HpkPoE8HqMHH1geL9 We’d be delighted to have you help shape this year’s workshop! 🎉 #AI4GOOD #TrustworthyAI #NeurIPS #AISafety

🎉 With the successful conclusion of our 1st Trustworthy AI4GOOD workshop at #ICML2026, we are delighted to share that its 2nd edition has been accepted for #NeurIPS2026 in Paris! 🎉🇫🇷 The workshop selection process was highly competitive: only 22% of 454 workshop proposals were accepted. We are grateful for the opportunity to bring the community together again! 🙌 Paris, here we come! 🇫🇷 ICML speakers: @Yoshua_Bengio, @OanaIgnatRo, @jzl86, @maksym_andr, Jenny Ni and @NamGoPro. Panel: @MilindTambe_AI, @lrhammond, Gopal Sarma and @ARGleave. Organizers: @TerryJCZhang, @ZhijingJin, @radamihalcea, @MilindTambe_AI, David Lie, @_agirlyengineer, @davidguzman1120, @ChanglingXavier, @Jerick1380, Prakhar Gupta, @vantru0ng, @EttoreGran, He (Shawn) Shuang, @ozzaney0101, Kexin Li and Wenjun Qiu. Thank you for making our first edition unforgettable!🙏 Thank you for making AI4GOOD possible! 💙 trustworthy-ai-for-good.gith…

Our Jinesis Lab at the University of Toronto is bringing three exciting papers to #COLM2026! 🎉 These projects push the frontiers of #AISafety, #AgentSecurity, and #AIForScience.🤖 Huge congratulations to all collaborators and co-authors! Papers: 🛡️ODILE: Orthogonal Disruption of Injected Tool-Call Embeddings for Agentic Prompt Injection Defense 🔭Stargazer: A Scalable Model-fitting Benchmark Environment for AI Agents under Astrophysical Constraints ⚠️One Word at a Time: Incremental Completion Decomposition Breaks LLM Safety @UofT,@VectorInst,@EuroSafeAI,@ETH_en,@MPI_IS,@UMich

🌟 What an incredible experience at #ICML2026! 🌟 Our team at Jinesis Lab had a fantastic time presenting research across several exciting and important areas: 🤝 Multi-agent LLMs 🧠 Causal reasoning 🛡️ AI safety We were proud to share this work alongside our collaborators and to engage with so many researchers from across the machine learning community. 💡 Just as valuable as presenting our own work was learning from the research others brought to ICML. From thought-provoking talks and innovative poster presentations to insightful discussions and spontaneous hallway conversations, the conference was full of ideas that challenged our thinking and opened new directions for future work. ✨ We are grateful to everyone who attended our presentations, visited our posters, shared feedback, and took the time to discuss their own research with us. 🙌 A huge thank-you to our lab members, collaborators, and the broader ICML community for making the experience so memorable. We are leaving inspired, energized, and excited to build on the ideas and connections formed throughout the conference. 🌍🔬🚀 #ICML #MachineLearning #ArtificialIntelligence #MultiAgentSystems #LLM #CausalReasoning #AISafety #ResponsibleAI #AIResearch #ResponsibleAI #AIResearch

🎉✨ The Trustworthy AI for Good Workshop at ICML 2026 was a huge success! ✨🎉 We are incredibly grateful to everyone who joined us in Seoul 🇰🇷 for a full day of inspiring research, thoughtful discussions, and meaningful connections around building AI systems that are both trustworthy and socially beneficial. 🤖🌍💡 A heartfelt thank-you to our incredible keynote speakers: 🎤 @Yoshua_Bengio, @OanaIgnatRo, @jzl86, @maksym_andr, Jenny Ni, Naman Goyal Your insights, perspectives, and thought-provoking ideas made the workshop truly memorable. 🌟🧠 A special thank-you to our outstanding panelists: 💬 @MilindTambe_AI, @lrhammond, Gopal Sarma, @ARGleave And to our wonderful moderator, @ZhijingJin, for leading such an engaging and insightful conversation. 🎙️ We are also deeply grateful to all our oral and poster presenters, reviewers, organizers, volunteers, sponsors, and every attendee who contributed questions, ideas, feedback, and enthusiasm throughout the day. 🚀 The energy of this community reinforced the importance of bringing together: 🛡️ AI safety 🌍 AI for social good ⚖️ AI policy and governance 🤝 Cooperative AI 📰 Information integrity 🏛️ Civic discourse Thank you for making Trustworthy AI for Good @ #ICML2026 such a memorable and impactful event! 🎊 We look forward to continuing the conversation, strengthening this community, and building on the connections formed at the workshop. 🤝 #ICML2026 #AIForGood #TrustworthyAI #AISafety #ResponsibleAI #MachineLearning #CooperativeAI #AIResearch #TechForGood #ArtificialIntelligence

🚨 Thrilled to share that our lab will be presenting the 🏆 Best Paper at the NExT-Game Workshop at #ICML2026 today! 🎤 When Agents Lie: Premeditation, Persistence, and Exploitation in Repeated Games 🏆 Best Paper @ NExT-Game Workshop 📍 Conference Room S307 📅 Fri, Jul 10 🕐 13:00–13:20 KST Authors: @JerickShi @TerryJCZhang @bschoelkopf @conitzer @ZhijingJin 🤖 We introduce a three-stage endogenous promise protocol for repeated multi-agent games that asks not only whether LLM agents honor their public commitments when they can privately deviate, but also how model-on-model composition influences premeditated deception and persistent exploitation. 📊 Across six canonical games spanning binary and numerical action spaces, our evaluation of frontier models (GPT-5.2, Llama-4-Maverick, Claude-Opus-4.6) reveals: 🔹 Over 90% of promise-breaking instances are premeditated in agents' private plans. 🔹 Mixed-model groups with mismatched communication frameworks create systemic, persistent payoff gaps of up to 5.00 points from Round 0. 📄 Paper: openreview.net/forum?id=v8nY… #MultiAgentSystems #LLMs #GameTheory #AI #ICML2026

Excited to share more of our workshop papers today, July 11, at #ICML2026!📍🇰🇷📷 🔧AIWILD (⭐Oral⭐) AF-ARENA: A Multi-Dimensional Evaluation Suite for Alignment Faking 🗓️ 10:10–10:40 AM KST 📍Hall B2. 🔗openreview.net/forum?id=vFqn… 🔧AI4Math Proving Your Way to Cooperation: Formalizing Proof-Based Open Source Game Theory in Lean 📍Room HALL D1 🔗openreview.net/forum?id=Wc5T… 🔧AI4Physics Stargazer: A Scalable Model-fitting Benchmark Environment for AI Agents under Astrophysical Constraints 📍Conference Room S402 🔗aips-uoft.github.io/Stargaze… 🔧NexT-Game GT-HarmBench: Benchmarking AI Safety Risks Through the Lens of Game Theory 📍Conf. room S307 🔗openreview.net/forum?id=F0Dz… 🔧Pluralistic Alignment The Wedge Questions: Latent Cultural Boundaries in LLMs via Persona Projection Divergence 📍Room 403, Board #4613 🔗openreview.net/forum?id=zHQu… Huge thanks to all collaborators, co-authors, organizers, and workshop communities — looking forward to many great discussions at #ICML 🚀

Thrilled to share that our lab will present the 🏆Best Paper🏆of RLxF Workshop @ #ICML2026 today! 📄 Transferability for General Reasoning: An Automated Curriculum for Multi-Domain LLM RL 📍 GRAND BALLROOM 101-102 🗓️ Fri, Jul 10 KST 🕚 4:00 PM – 5:00 PM KST 🎓 Authors: @_yongjinny, @Jiarui_Liu_, @yinghui_he_, @leczhang, @bschoelkopf, and @ZhijingJin We introduce Transfer-Aware Curriculum (TAC), an automated curriculum for multi-domain RLVR that asks not only which domain is learnable right now, but also which domain’s gradients transfer well to the rest of the reasoning suite. 🧩 Across math, code, logic, simulation, table reasoning, and STEM, TAC achieves the best macro-averaged accuracy on both Qwen3-1.7B and Llama3.2-3B, improving over strong curriculum baselines with <1% wall-clock overhead. 📐 Huge thanks to all collaborators, reviewers, and the RLxF organizers — and please stop by to chat if you’re at #ICML2026! 🚀 📄 Paper: arxiv.org/pdf/2606.25178 📎 Code: github.com/YangYongJin/trans… #ICML #ICML2026 #RLxF #ReinforcementLearning #LLM #Reasoning #RLVR

Excited to share our workshop papers being presented TODAY at #ICML2026 in Seoul 🇰🇷✨ Please stop by the posters and chat with us! 🔧 FoGen 📄 Test of Time: Rethinking Temporal Signal of Benchmark Contamination 🗓️ 9:10–10:00 AM, 2:00–2:50 PM KST 📍 ROOM 318 🤝 AI4GOOD 🌟Spotlight🌟 📄 Multi-Agent AI Systems Need Institutional Design, Not Just Model-Level Alignment 🗓️ 11:25 AM – 1:00 PM KST 📍 GRAND BALLROOM 103 🔬 AI4Research 📄 Causal AI Scientist: Towards End-to-End Causal Inference with Large Language Models 🗓️ 11:50 AM – 1:00 PM KST 📍 AUDITORIUM 🚨 FAGEN 📄 What Game-Theoretic Benchmarks Miss: Strategic Silence in Multi-Agent LLMs 🗓️ 12:00–2:00 PM KST 📍 GRAND BALLROOM 104-105 🤝 AI4GOOD 📄 Mechanism Design Is Not Enough: Prosocial Agents for Cooperative 📄 CoopEval: Benchmarking Cooperation-Sustaining Mechanisms and LLM Agents in Social Dilemmas 📄 Weight-Level Defenses Improve LLM Agent Adversarial Robustness 📄 Evaluating Cooperation in LLM Social Groups through Elected Leadership 📄 Multi-Agent AI Systems Need Institutional Design, Not Just Model-Level Alignment 🗓️ 4:20–5:00 PM KST 📍 GRAND BALLROOM 103 Huge thanks to all collaborators, co-authors, organizers, and workshop communities — looking forward to many great discussions at #ICML2026 🚀