Excited to share our #ACL2023NLP (#NLProc) paper on "Information Synchronization Across Multilingual Semi-Structured Tables"! 📚🔍 We explore the problem of Information Synchronization across multilingual tables and construct a large-scale dataset InfoSync. #NLPResearch -1/n

Excited to share our #ACL2023NLP (#NLProc) work on "Evaluating Inter-Bilingual Semantic Parsing for Indian Languages" appearing in @5thnlp4convai workshop. We propose IE-SEMPARSE, an Inter-bilingual Seq2seq Semantic parsing dataset for 11 Indian languages. - 1/n

I’ll be presenting our work “Verifying Annotation Agreement without Multiple Experts: A Case Study with Gujarati SNACS” as a virtual poster on Tuesday at #ACL2023 and in-person at LAW on Thursday. Joint work with Vivek Srikumar Paper: tinyurl.com/3989kvnp (1/3)

👏🔥our paper received Distinguished Paper award !

A Zero-Shot Language Agent for Computer Control with Structured Reflection paper page: huggingface.co/papers/2310.08… Large language models (LLMs) have shown increasing capacity at planning and executing a high-level goal in a live computer environment (e.g. MiniWoB++). To perform a

.Hugging Face appreciation at UtahNLP baking party 🤗🎄❤️☃️

New preprint 🚨 "Do LLM predictors provide structurally consistent outputs in the zero- and few-shot regime?" Our new work "Promptly Predicting Structures: The Return of Inference" shows that they do not, and we show how to fix it. (1/n) 🧵

Introducing SIMA: the first generalist AI agent to follow natural-language instructions in a broad range of 3D virtual environments and video games. 🕹️ It can complete tasks similar to a human, and outperforms an agent trained in just one setting. 🧵 dpmd.ai/3TiYV7d

🤗➕🏔️ UtahNLP is now organized on the Hugging Face hub I recommend you 👀 it huggingface.co/utahnlp

Excited to introduce our new paper BLINK! It’s a new benchmark for MLLMs, focusing on visual perception capabilities. We show that there’s still a gap between SOTA MLLMs and human performance in 14 tasks that can be solved by humans within a blink~

[AI] Devil's Advocate: Anticipatory Reflection for LLM Agents H Wang, T Li, Z Deng, D Roth, Y Li [Google DeepMind] (2024) arxiv.org/abs/2405.16334 - Proposes a novel approach that integrates introspection into LLM agents to enhance their consistency and adaptability in solving

Multiple Reflections NOT helping much? Tired of changing plans and NOT seeing utmost effort in their execution? Introducing Devil’s Advocate 😈: Equipping LLM Agents with *Anticipatory* Reflection before action execution #LLM #Agent #AI #ML arxiv.org/pdf/2405.16334…

Reflection doesn't have to be post-hoc. We show that agent can benefit from "anticipatory" failures. An extra bonus of doing so is that reflective trials can now run in parallel.

NeurIPS’24 authors: if you are desk rejected due to a missing checklist, add your email to this appeal letter! docs.google.com/document/d/16_… Getting desk rejected after filling out the checklist form carefully in OpenReview… This does not make any sense!

Congratulations to the authors of the “Rich Human Feedback for Text-to-Image Generation” paper, which received the #CVPR2024 Best Paper Award. Check out the paper at: arxiv.org/pdf/2312.10240

Are compressed LLMs less toxic and biased against different demographic groups❓In this new📜, we study 4 pruning methods and 3 quantization methods and evaluate on 7 bias/toxicity benchmarks. arxiv.org/abs/2407.04965 (Un)surprising answer is: they are not less toxic/biased

Thrilled to know that our paper on Scaling Laws for Dense Retrieval has won the #SIGIR2024 Best Paper Award! 🏆Our study reveals a power-law scaling of dense retrieval models, which can help optimize training and resource allocation. Huge thanks and congrats to all collaborators!

Got a picture that isn't quite right? Try our native image generation in Gemini Flash 2.0. "Can you remove the stuff on the couch?". "Can you make the curtains light green?" "Can you put a unicorn horn on the person in the green pants?" Editing in human language, not image

Glad we launched => aistudio.google.com

Think you know Gemini? 🤔 Think again. Meet Gemini 2.5: our most intelligent model 💡 The first release is Pro Experimental, which is state-of-the-art across many benchmarks - meaning it can handle complex problems and give more accurate responses. Try it now →