Frontier models have become excellent at understanding videos. But what happens when we test them outside the comfort zone of Western, English-centric data? In our #CVPR2026 (Highlight) work, we pushed these models to their limits to see if they can function effectively in diverse global contexts. The results? They are struggling. Work done with @NagraniArsha @skawshik11 @Harman26Singh @dinesh_tewari1 @0xtob @CordeliaSchmid Anelia Angelova @shachi_dave (1/7)

Optimize pretraining not just for loss, but for robustness to future updates. The "best" base model does not always make the best final model. 📄 More in the paper: scaling results, Hessian analysis, and practical recipes arxiv.org/abs/2605.02105 Huge thanks to my collaborators: @CatherineL11638 @goyalsachin007 @jacspringer @AdtRaghunathan 9/9

Thrilled to share that our paper on "Interpreting and Controlling Model Behavior via Constitutions for Atomic Concept Edits" has been accepted at AISTATS 2026! 🚀🚀 Read more about how input mutations can be mapped to interpretable behavioral insights. arxiv.org/abs/2602.00092 🧵

📢 #LCS2 is coming to Morocco ✈️ Happy to announce that two papers from our lab have been accepted to #EACL2026. Congratulations to all the authors, great start to the year! 🙌 #IITDelhi #EACL2026 #ACLCommunity #NLProc #AIResearch @Tanmoy_Chak

Thrilled to note that we are keeping the tradition of the awesome AI residency program alive in a new avatar: pre-doc researcher program at GDM-Blr -- with some amazing work done by our recent predocs including @gautham_ga_ @pranamyapk @puranjay1412 @sahilgo6801 @swaroopnath6 If you want to join this program, please apply here: google.com/about/careers/app…

Kicking off the year with a bang -- 4 papers accepted in prestigious venues this month! #ICLR2025 -- 𝐋𝐋𝐌 𝐜𝐨𝐦𝐩𝐫𝐞𝐬𝐬𝐢𝐨𝐧: We introduce 𝐏𝐫𝐮𝐧𝐞𝐍𝐞𝐭, a novel, dataset-free policy learning approach to model pruning, achieving high compression efficiency and performance retention, demonstrated by compressing LLaMA-2-7B with over 80% zero-shot accuracy retention at a 30% compression ratio. @iclr_conf URL: shorturl.at/HEO7O #𝐍𝐀𝐀𝐂𝐋2025 -- 𝐈𝐧𝐯𝐞𝐬𝐭𝐢𝐠𝐚𝐭𝐢𝐧𝐠 𝐦𝐮𝐥𝐭𝐢𝐥𝐢𝐧𝐠𝐮𝐚𝐥 𝐥𝐨𝐧𝐠-𝐜𝐨𝐧𝐭𝐞𝐱𝐭 𝐛𝐞𝐡𝐚𝐯𝐢𝐨𝐫 𝐢𝐧 𝐋𝐋𝐌𝐬: We introduce 𝐌𝐋𝐍𝐞𝐞𝐝𝐥𝐞, the first systematic evaluation of multilingual long-context retrieval in LLMs, revealing significant performance variations across languages and context positions, with insights to guide future evaluations. @naaclmeeting Preprint: lnkd.in/gtRAXjmh 𝐍𝐀𝐀𝐂𝐋'25 -- 𝐂𝐨𝐮𝐧𝐭𝐞𝐫𝐬𝐩𝐞𝐞𝐜𝐡 𝐞𝐯𝐚𝐥𝐮𝐚𝐭𝐢𝐨𝐧 𝐛𝐞𝐧𝐜𝐡𝐦𝐚𝐫𝐤 𝐚𝐧𝐝 𝐦𝐞𝐭𝐫𝐢𝐜𝐬: We introduce 𝐂𝐒𝐄𝐯𝐚𝐥, a dataset for evaluating counterspeech across four dimensions and a prompt-based framework using auto-calibrated CoT, offering better alignment with human judgment than traditional metrics. @naaclmeeting 𝐍𝐚𝐭𝐮𝐫𝐞 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞: In collaboration with AIIMS (All India Institute of Medical Sciences, New Delhi), NIMHANS, Bangalore and other NGOs, we wrote how GenAI can potentially empower multisectoral suicide prevention efforts, particularly in resource-constrained settings like India. @NatMachIntell