Tanmay Parekh @tparekh97 Twitter profile | Pikagi

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Tanmay Parekh

@tparekh97

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PhD student @UCLA | Intern @AIatMeta @AmazonLab126 | MLT @LTIatCMU | Applied Scientist @amazonIN | BTech @iitbombay

Joined April 2020

Don't wanna be here? Send us removal request.

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@tparekh97

Tanmay Parekh

6 months

🦠How to avoid a future COVID pandemic? 🔍How to detect epidemics early? Excited to share our latest work SPEED - an Event Detection framework to extract epidemic-related events from Tweets and can provide breakthrough early warnings for the unseen epidemic of Monkeypox! 🤯😱

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@tparekh97

Tanmay Parekh

3 months

Excited to share that I’ll be starting my internship at @AIatMeta in the GenAI team from tomorrow! I’ll be based off in Bellevue for the next 3.5 months. Please say a hi if you are around, would love to catch up! 👋🏻

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@tparekh97

Tanmay Parekh

1 year

📢 Introducing GENEVA: Generalizability Benchmarking Dataset for Event Argument Extraction, a super diverse and high coverage EAE dataset with 115 event types and 220 argument roles. Paper: Github: Accepted at #acl2023 main (1/n)

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@tparekh97

Tanmay Parekh

6 months

🔍🚨How to improve multilingual performance on structured prediction tasks? Excited to share our latest work CLaP - a label projection technique utilizing LLMs to do contextualized machine translation, improving two tasks in 47 languages including 10 extremely low-resource ones!

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@tparekh97

Tanmay Parekh

4 years

Very excited to share our @conll_conf work done with @emilypahn , Yulia Tsvetkov, and Alan Black. We study how machines can influence human behavior in code-switched conversations by means of linguistic entrainment. #conll2020 #emnlp2020

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@tparekh97

Tanmay Parekh

5 months

😇😇 Will be honoured to speak at @USC_ISI about our societally impactful application of epidemic prediction through event extraction. 🚨Join in to know how we can prevent any future pandemic!!

@HJCH0

Justin Cho 조현동

5 months

📢 Next Thursday (5/9) is ISI's last NL seminar for this spring semester and we have Tanmay Parekh @tparekh97 from UCLA giving us a talk on "Event Extraction for Epidemic Prediction" The talk will be at 11AM PST and is open to the public via Zoom, please email us ahead of time

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@tparekh97

Tanmay Parekh

7 months

Happy birthday @VioletNPeng !! Socials at our lab are lit 🔥 Thanks @sidilu_pluslab for this amazing gift 🎁

@uclanlp

uclanlp

8 months

Happy birthday @VioletNPeng and PlusLab members! 🎂🎊 And congrats to @tparekh97 for winning the Best Presenter Award! 🎉

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@tparekh97

Tanmay Parekh

4 months

Good morning NAACL folks! Today, I’ll be presenting my work on a simple and cute way of utilising LLMs for multilingual data augmentation for structured prediction task! Come check out @ 9am in the poster session! #NAACL2024

@tparekh97

Tanmay Parekh

6 months

🔍🚨How to improve multilingual performance on structured prediction tasks? Excited to share our latest work CLaP - a label projection technique utilizing LLMs to do contextualized machine translation, improving two tasks in 47 languages including 10 extremely low-resource ones!

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Tanmay Parekh

4 months

I will be at #NAACL2024 next week. I’ll be talking about two of my event extraction related works: SPEED and CLaP. Looking forward to meeting the community! 🇲🇽

@tparekh97

Tanmay Parekh

6 months

🦠How to avoid a future COVID pandemic? 🔍How to detect epidemics early? Excited to share our latest work SPEED - an Event Detection framework to extract epidemic-related events from Tweets and can provide breakthrough early warnings for the unseen epidemic of Monkeypox! 🤯😱

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@tparekh97

Tanmay Parekh

4 months

Will be presenting our work today on Epidemic Prediction using Event Extraction @ 2pm in Don Alberto 3 hall. Join in to know more! #NAACL2024

@tparekh97

Tanmay Parekh

6 months

🦠How to avoid a future COVID pandemic? 🔍How to detect epidemics early? Excited to share our latest work SPEED - an Event Detection framework to extract epidemic-related events from Tweets and can provide breakthrough early warnings for the unseen epidemic of Monkeypox! 🤯😱

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@tparekh97

Tanmay Parekh

11 months

Thanks for joining and a day full of fun and learning! Until next time! :)

@socalnlp

SoCal NLP Symposium

11 months

🏝️And that’s a wrap! Thank you everyone for travelling or driving to Los Angeles/ @ucla and #SoCalNLP2023 ! It was a fun day with great discussions, networking and some gossip strewn in from recent news 🤭 See you all next year!!!

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@tparekh97

Tanmay Parekh

4 months

Our work has been accepted at #ACL2024 Findings. Check it out for all of your event extraction needs!

@kuanhaoh_

Kuan-Hao Huang

11 months

Working on event extraction?🧐 Check out our latest event extraction benchmark project! We propose 𝙏𝙚𝙭𝙩𝙀𝙀, a standardized, fair, and reproducible benchmark for event extraction. Webpage: Github:

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@tparekh97

Tanmay Parekh

1 year

📢 This is a great opportunity to publicise your work, meet potential collaborators, and network! You can simply submit a 2-page in-progress work or an already accepted/under review work as well. #SoCalNLP #CallForPapers

@lupantech

Pan Lu ✈️ COLM 2024

1 year

📢 Attention #NLPoc community! Submit and showcase your research at the 4th Southern California Natural Language Symposium (SoCal NLP) 📜 🗓️ Submission Deadline: Oct. 21, 2023, 11:59 PM PT 🔗 More info: #SoCalNLP #CallForPapers

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@tparekh97

Tanmay Parekh

4 months

Having worked with @kuanhaoh_ for 3 years, I can vouch for his experience and long-term vision. I also greatly admire his coding skills. For all new students, will strongly suggest to consider talking to him once for future PhD prospects!

@kuanhaoh_

Kuan-Hao Huang

4 months

I'll miss #NAACL2024 next week due to my visa status. However, feel free to talk to @tparekh97 about our latest work on event extraction and cross-lingual transfer! I'm also seeking students to join my group at TAMU. Interested? Fill out this Google form!

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@tparekh97

Tanmay Parekh

5 months

Taking video generation to the next level 🔥💯

@hbXNov

Hritik Bansal

5 months

📢Can you generate long multi-scene videos from existing text-to-video (T2V) generative models? Happy to introduce Time-Aligned Captions (TALC), a fundamental framework that allows multi-scene video generation without any further training 🤯 Paper: 🧵👇

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@tparekh97

Tanmay Parekh

4 months

Check out this amazing work by @hbXNov on evaluating the physical commonsense of video generation models. Lots of interesting findings!

@hbXNov

Hritik Bansal

4 months

🚨Can existing video generative AI 🎥 replace graphic designers in Hollywood 🎬? The answer is NO 🚫 📢 We present VideoPhy, and find that the generated videos lack physical commonsense – making them poor physical world simulators 🤖 Paper: 🧵👇

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@tparekh97

Tanmay Parekh

6 months

Do LLMs understand sound or do they simply do next-token prediction. Check out this new work challenging LLMs by @suvarna_ashima

@suvarna_ashima

Ashima Suvarna🌻

@suvarna_ashima

6 months

📢 We propose a new benchmark called PhonologyBench for testing how well LLMs perform on three tasks that require sound knowledge : phonemic transcription, counting syllables, and listing possible rhymes. w/ Harshita Khandelwal, @VioletNPeng 1/3

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@tparekh97

Tanmay Parekh

6 months

8/N 🙏 Huge thanks to my advisors @kaiwei_chang and @VioletNPeng . Immense gratitude to my awesome mentors and collaborators @IHung_Hsu and @kuanhaoh_

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@tparekh97

Tanmay Parekh

4 years

Happening now. @conll_conf from 11:45 - 1:45 PM EST

@tparekh97

Tanmay Parekh

4 years

Very excited to share our @conll_conf work done with @emilypahn , Yulia Tsvetkov, and Alan Black. We study how machines can influence human behavior in code-switched conversations by means of linguistic entrainment. #conll2020 #emnlp2020

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@tparekh97

Tanmay Parekh

4 years

This course was a great success. Covered a broad range of topics complemented by in-depth class discussions. The guest lecturers were the icing on the cake. Enjoyed working with the team and it was a big learning experience indeed!

@gneubig

Graham Neubig

4 years

We have finished uploading our 23 class videos on Multilingual NLP: Including two really great guest lectures: NLP for Indigenous Languages (by Pat Littell, CNRC): Universal NMT (by Orhan Firat, Google):

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@tparekh97

Tanmay Parekh

4 months

Flexible inference capability for your vision language models 💪💯

@gordonhu608

Wenbo Hu

4 months

How to pick a good number of visual tokens? Too few, you have poor performance; too many, you need quadratically more compute. In this work, we introduce a model that works with an elastic number of tokens. arXiv:

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@tparekh97

Tanmay Parekh

1 year

“Maybe the only thing special about people is how special they think they are” - closing remarks by Hinton #ACL2023

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@tparekh97

Tanmay Parekh

6 months

🎉🎊Our work has been accepted and will appear at #NAACL2024 . Hope to discuss more about our work in Mexico City! 🇲🇽

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@tparekh97

Tanmay Parekh

11 months

Check out this work by Hritik on video-text alignment

@hbXNov

Hritik Bansal

11 months

📢 📽✍️We introduce VideoCon, a video-text dataset for training SOTA alignment model. It resolves a typical issue in video-text alignment models that struggles with robustness. w/ @YonatanBitton , Idan Szpektor, @kaiwei_chang , @adityagrover_ 🧵 1/

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@tparekh97

Tanmay Parekh

6 months

8/N Shoutout to my mentors @WeiWang1973 @VioletNPeng @kaiwei_chang @kuanhaoh_ and my amazing undergrad team: Anh Mac, Jiarui Yu, Yuxuan Dong, Syed Shahriar, Bonnie Liu and Eric Yang

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Tanmay Parekh

6 months

6/N ⬆️Larger LLMs: Utilizing larger LLMs for CLaP strongly improves the low-resource languages, while performance for medium-to-high-resource languages remains similar. This highlights how CLaP can continually improve with improved and more advanced LLM capabilities.

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@tparekh97

Tanmay Parekh

6 months

5/N 👀Epidemic Prediction: Using events detected by our model, we provide epidemic warnings 4-9 weeks before the number of cases peaked and WHO issued a global health concern warning. We also show that our model predictions are relevant to the Monkeypox epidemic.

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@tparekh97

Tanmay Parekh

7 months

Please consider voting for Kai-Wei

@kaiwei_chang

Kai-Wei Chang

7 months

I am honored to be nominated by SIGDAT (the org that oversees EMNLP) to run for VP-elect with other awesome candidates who share the goal of improving our community. Please check your email to vote by 3/24.🗳️ See details:

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@tparekh97

Tanmay Parekh

6 months

3/N 📊 Event Detection: Our trained models are better than any other data-transfer or zero-shot model. Furthermore, we show significant improvements over the previously utilized keyword-based and the new LLM-based methods.

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@tparekh97

Tanmay Parekh

6 months

7/N More details can be found here - 📝 Paper: 🛠️ Code and Data:

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@tparekh97

Tanmay Parekh

6 months

5/N 📊Better than LLM Inference: Compared to utilizing LLMs directly for inference on the target languages, we observe that LLM usage in CLaP provides significantly stronger improvements up to 66 F1 points (for Bengali).

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@tparekh97

Tanmay Parekh

10 months

Meet our folks at EMNLP!

@uclanlp

uclanlp

10 months

Excited for #EMNLP2023 ? #UCLANLP & members @cfyang58 @Wade_Yin9712 @FanYin63689862 @kamath_amita @DiWu0162 @P_N_Kung @telinwu @sunjiao123sun_ @HaoyiQiu @yufei_t @yu_bryan_zhou will present a range of work on NLG, fairness, instruction tuning, and multi-modality. 🧵👇 (1/18)

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@tparekh97

Tanmay Parekh

6 months

7/N For future references - Paper: Code:

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GitHub - PlusLabNLP/CLaP: Code for our NAACL-2024 paper "Contextual Label Projection for Cross-Li...

Code for our NAACL-2024 paper "Contextual Label Projection for Cross-Lingual Structured Prediction" - PlusLabNLP/CLaP

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@tparekh97

Tanmay Parekh

6 months

2/N 📄 Dataset: We simplify existing epidemiological ontologies into seven core events frequently discussed on Twitter. Six expert annotators annotate to create our dataset of 2.2K COVID-based epidemic events. We evaluate in a cross-disease setting on Monkeypox, Zika, and Dengue.

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@tparekh97

Tanmay Parekh

6 months

1/N ❓Formulation: We introduce a new paradigm of contextual machine translation (i.e. translation with a context) to do label projection by emphasizing the label translation to be conditional on the translated sentence to ensure better consistency.

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@tparekh97

Tanmay Parekh

8 months

One hub for all Event Extraction needs! Do check out our extensive benchmarking. We also tried five different LLMs and they perform poorly at this task. Also, it's completely open-source, so feel free to benchmark and add your models to the hub!

@kuanhaoh_

Kuan-Hao Huang

11 months

Working on event extraction?🧐 Check out our latest event extraction benchmark project! We propose 𝙏𝙚𝙭𝙩𝙀𝙀, a standardized, fair, and reproducible benchmark for event extraction. Webpage: Github:

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@tparekh97

Tanmay Parekh

4 years

In our analysis, we find that users find the code-switching agent to be more engaging. Further, making the agent informal by adding some discourse markers makes it more native to the users.

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@tparekh97

Tanmay Parekh

6 months

7/N 💡 Extremely Low Resource Languages: CLaP also has the potential to improve extremely low-resource languages, as evidenced by our experiments on NER for 10 languages from Africa and South America.

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@tparekh97

Tanmay Parekh

6 months

🎉 Our work has been accepted and will appear at #NAACL2024 . Hope to meet and discuss more about our work in Mexico City! 🇲🇽

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@tparekh97

Tanmay Parekh

6 months

4/N ⏳ Early Detection: In fact, our COVID-only trained model performs better or at par with models trained on limited target epidemic data. This signifies the utility of our framework for early epidemic detection when no or limited target epidemic data is available.

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@tparekh97

Tanmay Parekh

6 months

3/N 🔁 Evaluation: Intrinsically, CLaP-generated data provides the strongest accuracy while maintaining good faithfulness. This highlights the strong data generated using CLaP.

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@tparekh97

Tanmay Parekh

4 years

We develop a generalized bilingual dialogue framework for data collection which can be utilized for other code-switching pairs too. We use AMT to collect the data for Hindi-English dialogues and release the dataset for future research.

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@tparekh97

Tanmay Parekh

6 months

2/N ⚙️ Model: We model contextual machine translation through large language models (LLMs) by incorporating the constraints as natural language instructions into the model and using two in-context examples. We use a small primarily English Llama2-13B model for our work.

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@tparekh97

Tanmay Parekh

6 months

Check out this new cool work on Joint Preference Optimization!

@hbXNov

Hritik Bansal

6 months

📢Humans are capable of providing preferences in similar, but non-identical contexts! So why restrict LLMs? Excited to introduce DOVE 🕊️, a new objective for aligning LLMs that optimizes preferences over joint instruction-response pairs. Paper:

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Tanmay Parekh

6 months

6/N 🔍 Disease Profiling: We also show the utility of our framework for disease profiling by mapping the proportions of events detected. These profiles are correlated with various recent findings of these diseases.

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@tparekh97

Tanmay Parekh

6 months

1/N ❓Formulation: We first re-formulate epidemic prediction as an event detection task by aggregating the number of detected events over time. We characterize early warnings by a sharp increase in the number of detected events.

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@tparekh97

Tanmay Parekh

1 year

FYI: Deadline Extended. We are accepting submissions until Oct 23 11:59 PM PT #SocalNLP

@socalnlp

SoCal NLP Symposium

1 year

Dear all, We will extend the submission deadline for #SocalNLP23 to *Oct 23* 11:59 PM PT. If you have a paper accepted or submitted to recent conferences, you may submit it as is to the symposium Also, registration is now open

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Tanmay Parekh

6 months

4/N 📈 Evaluation: On downstream tasks, CLaP improves over the best baseline on EAE by 2.4 F1 and NER by 1.4 F1 points averaged over 39 languages. It's grossly surprising how LLama2-13B primarily focused on English can still understand other languages including low-resource ones!

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@tparekh97

Tanmay Parekh

1 year

Utilizing the EAE ontology mappings, we transform FrameNet into GENEVA, a diverse, dense, and high-coverage EAE dataset. We conduct several human validation steps to ensure the high annotation quality and comprehensiveness of our dataset. (5/n)

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@tparekh97

Tanmay Parekh

4 years

This work motivates the development of agents to follow similar accommodation when conversing with humans. It also provides more resources for the development of dialogue agents that can cater to code-switched and multilingual communities.

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@tparekh97

Tanmay Parekh

1 year

Shoutout for the great effort by our team @IHung_Hsu @kuanhao_ @VioletNPeng @kaiwei_chang @uclanlp #pluslab Hope to reach out to all at #acl2023 (n/n)

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@tparekh97

Tanmay Parekh

1 year

First, we create a large and diverse EAE ontology by exploiting shared properties of SRL and EAE. Through extensive human annotations, we transform FrameNet, an SRL dataset into a large EAE ontology with 179 events and 362 argument roles. (3/n)

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@tparekh97

Tanmay Parekh

4 years

Finally, we observe strong trends in accommodation of language choice. Basically, users use English for referring to fruits if the agent uses English for fruits. Also, humans also adapt the style of code-switching to a great extent.

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@tparekh97

Tanmay Parekh

4 years

For knowing more interesting facts and cool analysis or just asking questions, you can visit us at @conll_conf on Nov 19 from 11:45-13:45 EST

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@tparekh97

Tanmay Parekh

1 year

Previous EAE datasets only focused on entity-based arguments. We introduce non-entity argument roles for the first time for EAE, with about 37% of our argument roles being non-entities. (4/n)

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@tparekh97

Tanmay Parekh

1 year

Overall, in our work, ➕ We build a new comprehensive and diverse EAE ontology ➕ We introduce a generalizability benchmarking dataset GENEVA ➕ Provide benchmarking results for various models including GPT highlighting the challenges in GENEVA. (2/n)

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@tparekh97

Tanmay Parekh

4 years

@Saikallis9012 I remember you telling me this even for planning the day. And it really helps! Worst case, you finish early and feel good about yourself.

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@tparekh97

Tanmay Parekh

1 year

We design four generalizability benchmarking test suites using GENEVA: (1) Low resource, (2) Few-shot, (3) Zero-shot, and (4) Cross-type transfer. They assess models' ability to learn from limited data and generalize to unseen event types and argument roles. (6/n)

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@tparekh97

Tanmay Parekh

1 year

Under similar zero-shot settings, the SOTA model DEGREE achieves a mere 39% F1 score on GENEVA while 53% on the ACE dataset. This shows how GENEVA poses additional challenges and can be attributed to the presence of non-entity arguments. (8/n)

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@tparekh97

Tanmay Parekh

3 years

@Das8Ankush Many many congratulations! 🎉🎉

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@tparekh97

Tanmay Parekh

1 year

We evaluate 8 different models of various model families like traditional classification-based, question-answering-based, generation-based models, and GPT-styled models on the different test suites. We observe that generation-based models provide the best generalization. (7/n)

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@tparekh97

Tanmay Parekh

1 year

You can even submit your under-review works and get free publicity for your work! Don't miss out! #SoCalNLP

@socalnlp

SoCal NLP Symposium

1 year

Folks, SoCalNLP Symposium poster submissions are due soon -- *Oct 21*! 🏖🌞 🔗 CfP details:

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@tparekh97

Tanmay Parekh

1 year

We also benchmark GPT3.5-turbo on the zero-shot setting where it only achieves an F1 score of 22%. This is significantly lesser than DEGREE's performance of 39% and shows how our dataset is challenging for LLMs in general. (9/n)

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@tparekh97

Tanmay Parekh

8 months

Check out this amazing work from @yixin_wan_

@yixin_wan_

Yixin Wan

8 months

DALL-E 3 seems to have reduced gender biases in single-person images. So, problem solved🥂? NOT YET!🤚 ⚠️We discovered the UNDERLYING GENDER BIASES in the Text-To-Image Model through a proposed Paired Stereotype Test(PST) evaluation framework. Full paper:

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@tparekh97

Tanmay Parekh

4 years

@dkaushik96 You can read "over 5500 pages" probably in 2 secs

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@tparekh97

Tanmay Parekh

6 months

@TuhinChakr @columbianlp @SmaraMuresanNLP @VioletNPeng Congratulations Dr. @TuhinChakr 🎉🎉

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Tanmay Parekh

4 years

@setlur_amrith @Saikallis9012 Congrats @setlur_amrith for the awesome work! Well deserved!

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@tparekh97

Tanmay Parekh

7 months

Want to extract specialized keywords from your text? Check out this work from our lab!

@DiWu0162

Di Wu

7 months

Delighted to introduce KPEval, a fine-grained semantic-based keyphrase evaluation framework with state-of-the-art reference-based metric and diverse application-oriented reference-free metrics. Paper: Toolkit:

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Tanmay Parekh

1 year

@kuanhao_ Congratulations! 🎉

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@tparekh97

Tanmay Parekh

3 months

Check out this amazing work by @IHung_Hsu on knowledge grounding!

@IHung_Hsu

I-Hung Hsu

3 months

🚀 New paper alert! Want to make your LLM's generation more credible and grounded on pieces of evidence? Our CaLM algorithm, presented at @ACL '24, leverages smaller LMs to achieve just that **unsupervisedly**! (1/n)

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@tparekh97

Tanmay Parekh

4 years

@khyathi_chandu Congrats khyathi!

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@tparekh97

Tanmay Parekh

3 years

@shrimai_ @nvidia @ctnzr Congrats Shrimai! All the best for your future ventures! 🎉🎉

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@tparekh97

Tanmay Parekh

2 years

@danish037 Congrats and all the best for your new journey! 💯💯

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@tparekh97

Tanmay Parekh

9 months

@hbXNov Congrats! 🎉

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@tparekh97

Tanmay Parekh

4 years

@ManishEarth @ServoDev Sorry to hear that. You have always been an inspiration to many. Good luck for your future endeavors too!

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@tparekh97

Tanmay Parekh

8 months

@sunjiao123sun_ @MaxMa1987 @VioletNPeng @jonathanmay @emilio__ferrara Congrats Jiao! 🎉🎉

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@tparekh97

Tanmay Parekh

4 years

@Ritam_Dutt @eaclmeeting I submitted and did get a notification. So I can confirm receiving the notification part here...

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@tparekh97

Tanmay Parekh

5 months

@kuanhaoh_ @TAMU Congratulations! I’m sure you’ll be a great advisor 🎉🎉🎉

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@tparekh97

Tanmay Parekh

4 years

@sid7954 Congrats! :D

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@tparekh97

Tanmay Parekh

3 months

@m2saxon @AIatMeta Yes sure! Let me DM you and we can coordinate 💪

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@tparekh97

Tanmay Parekh

1 year

Follow our official page to stay updated about further instructions! #SoCalNLP2023

@socalnlp

SoCal NLP Symposium

1 year

Hello World! 🙌🏼 #SoCalNLP2023 is back this year, to be held @UCLA ! 🏝️☀️ Keep an eye here for more announcements, but for now, our CfP is open! More details ⬇️ 🔗 📆Nov. 17, 2023

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