Ram Kadiyala @_1024_m

Let's get studious. 🏫 This month, the Cohere Labs Open Science Community ML Summer School returns! Join us to be part of a global community exploring the future of ML and hear from speakers across the industry. Register to save your spot today: cohere.link/xHeONbj We're looking forward to welcoming @_amirbar, Elizabeth Lingg, @irombie, Julia Kreutzer, @KatrinaL2899, Laurie Voss, @maximelabonne, @itsNVA7, @PuyuanPeng , @_1024_m, @SidYaeger, @SreyanG, Tushar Udeshi, Vivian White, Yash Mali 🔥 A huge thank you to our community leads for organizing this program @AhmadMustafaAn1, @Rafay_Mustafa1, @KanwalMehreen2, @PrahithaM, Anu Adesina, @VivekS100, and @rahul_narava! ✨

“What’s my approval rating?” - It’s bad Mr Prime Minister. It’s -43. It’s…it’s in the mud. “Could it get lower?” - I mean anything COULD happen but realistically- “Kill the ponies.” - Wha- “The ponies. The cute little ponies. Kill them.” - Sir, they’re endangered “Fuck ‘em. Make the call.”

Steven Swinford @Steven_Swinford

4 weeks ago

Exclusive from @oliver_wright Dartmoor ponies could be subject to mass culling to reduce the impact on biodiversity after a controversial ruling by the government’s environmental quango Natural England has demanded that all livestock grazing on the moor is reduced by about 75

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@aakrit Any context on what areas ?

What has been publicly “rolledback” may still privately be happening as there is no way to know what was degraded and whats not. Previously it was “accidental overlook” when it came to coding over several turns of chat via IDEs (ex: through cursor) where minor mistakes were added so a few more turns of usage could increase token usage. While most coding benchmarks arent multi-turn coding sessions via chat, this would have no impact on scores. Although the models are far better than what openAI or google offer currently, One should reduce dependence on whatever model is SOTA at a given time and limit the usage to harder tasks or the ones other models are failing to grasp/solve. Same applies for any tools, I personally wouldnt use claude/codex unless I absolutely have to, but regulary use the both of them via cursor or other IDEs

MTS @MTSlive

a month ago

SITUATION UPDATE: Anthropic is reversing its Fable 5 policy of covertly degrading performance for competing AI researchers, per Wired.

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@kenwuuuu Strands / Google ADK depending upon what cloud platform you are (going to be) using.

@therealoliulv @speedrun Unfortunately, this is something that exists out of the box for aws, some service companies have built this already. youtu.be/Cd71SbJ0I5M?si…

We have a bi-weekly meets and are open to contributions. No prior exp or publications are needed. We also offer co-authorship to contributors.

Cohere Labs @Cohere_Labs

2 months ago

🚀 Our community-led ML Agents group is kicking off a new collaborative project to build a Street Navigation Agent for more inclusive, region-aware local search. In many parts of the world, businesses exist physically — but not digitally. They're exploring how AI can use tools

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Will be there at the @ycombinator startup school. Open to discussing any potential matches/ideas on data/evals/agents.

Jared Friedman @snowmaker

3 months ago

Tomorrow. YC Startup School India.

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Congrats to everyone involved in Kaleidoscope, a cross-institutional collaboration accepted to ICLR 2026 🔥 A special shoutout to @mziizm who championed this collaboration from day 1. It is the first accepted paper for many of the collaborators who are first time authors.

Cohere Labs @Cohere_Labs

a year ago

🚀 We are excited to introduce Kaleidoscope, the largest culturally-authentic exam benchmark. 📌 Most VLM benchmarks are English-centric or rely on translations—missing linguistic & cultural nuance. Kaleidoscope expands in-language multilingual 🌎 & multimodal 👀 VLMs evaluation

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Many researchers join our community seeking mentorship, support, and a roadmap as they embark on their journeys. @_1024_m and @jebish7 did just this. Now, just 2 years later, they are creating these pathways for others, opening doors, and leading the way.

In 2025, our Open Science Community Leads showed what’s possible when AI research is built in the open. 38 leads, 17 programs, 125 guest speakers advancing open, collaborative AI across the world (find all talks here! cohere.link/uw1lvQQ). 🤯

(3/3) Improving Multilingual Capabilities with Cultural and Local Knowledge in Large Language Models While Enhancing Native Performance. arxiv.org/pdf/2504.09753 A Hindi-English bi-lingual LLM with over 140 checkpoints trained with variations in data distributions. Findings : - LLM-translated data can work as good as real data to address lack of data - Each task type has a different optimal data distribution amount, which could be determined by test runs on a subset of data. - LLM-generated thinking texts were made descriptive yet concise, this led to less emission (less token consumptions) during evals for text-generation tasks while providing better performance. Release : - Open Data, Models and 140 Checkpoints huggingface.co/collections/la… huggingface.co/1-800-LLMs

(2/3) Uncovering Cultural Representation Disparities in Vision-Language Models arxiv.org/pdf/2505.14729 huggingface.co/datasets/Biase… Key Highlights : - We test several VLMs at country/culture recognition task in 3 settings : Open-ended, MCQs with similar or neighbouring countries, MCQs with random countries - We also test them by image ablations (noise, rotations, greyscaling, etc..) Findings : - Country level biases do correlate with country wise availability of online data i.e more data or mentions >> less bias or misclassification. This contradicts the common assumption of western-favouritism. - Image perturbations affect biases in a very random way even among models belonging to the same family. - Language of prompt had negligible effect other than improving accuracy over countries that speak the language.

Three of our papers have been accepted at AACL 2025 @aaclmeeting (2 Main, 1 Findings). 1. DSBC : Data Science task Benchmarking with Context engineering arxiv.org/pdf/2507.23336 2. Uncovering Cultural Representation Disparities in Vision-Language Models arxiv.org/pdf/2505.14729 3. Improving Multilingual Capabilities with Cultural and Local Knowledge in Large Language Models While Enhancing Native Performance arxiv.org/pdf/2504.09753 Grateful to the co-authors @SidYaeger @Siddartha_10 @jebish7 @delliott @alexrs95 @_sumand @_srishtiyadav @KanwalMehreen2 This was made possible through research grants from @TraversaalAI @AnthropicAI @Cohere_Labs

Our open science community welcomes a new group focusing on agents, led by @_1024_m & @jebish7. They'll explore: 📊evaluation frameworks 🖥️agentic applications 🏇efficient systems ...via panel discussions and community-led projects. Join our community on this exploration.