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            @IELabGroup
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              The Information Engineering Group @ The University of Queensland (UQ) ๐ https://t.co/c9U1VHZKUt โถ๏ธ https://t.co/pWQiROb2sdโฆ
              
              Brisbane, Queensland
            
            
              
              Joined April 2018
            
            
           ๐ Excited to share the list of our @IELabGroup papers accepted at #SIGIR2025 @ACMSIGIR! Topics include efficiency in IR, domain-specific IR (SysRev, podcast), screenshot retrievers, hallucination detection, and more. See you in Padua ๐ฎ๐น! Details coming soon, stay tuned! 
          
                
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             The @IELabGroup is very active in IR research with publications across SIGIR, EMNLP, WebConf, WSDM, ECIR among other top venues. You will join a dynamic and collaborative research team, with strong support for your research and career development 
          
                
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             Come and join us at The University of Queensland. UQ is in sunny Brisbane, the 3rd most populated city in Australia, close to great beaches and forests. Brisbane is very lively and liveable; it will host the 2032 olympics. UQ ranks among the top-50 universities in the world. 
          
                
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             Me, @bevan_koopman and part of the team will be at @SIGIRConf 2024 if you want to chat about the postdocs. I also will be at @essir_eu #ESSIR2024 #SIGIR2024
          
          
                
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             Postdocs: we are seeking 2x postdocs for up to 3 years. In these positions you will develop your expertise and an emerging research profile in IR, NLP, and LLMs, with particular applications in the health domain. More info:  https://t.co/GtbwUoeDGY  Applications close on 2 August 
          
                
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             PhD scholarship: โThe Future of Search: Reducing the Environmental Impact of Large Language Models with Quantum Computing" -- You will be part of the joint PhD program b/w @UQSchoolEECS & @UniofExeter More info at  https://t.co/1ay05CDLwE  Quick, closes 28 June 
          
                
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             We have a PhD scholarship and 2 postdoc openings in the @IELabGroup team to work on Information Retrieval and LLMs. Come and join us! ๐งต 
          
                
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             It was great to have @jainprateek_ from @GoogleDeepMind visiting @UQSchoolEECS last week, and talking to us about Efficient and Elastic Large Models. Efficiency in LLM inference and elasticity of models certainly big ticket items to solve for improved LLM adoption @UQ_News
          
          
                
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             (2) this work breaks away from previous attempts to use generative LLMs as encoders by being the first method that can create dense representations in a zero-shot manner and without requiring finetuning 
          
                
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             (4) all code and results are publicly released (see  https://t.co/mq7VIDDOMb)  You can fully reproduce our results with just a few command lines as there is no expensive LLM training 
          
            
            github.com
              Prompting Large Language Models to Generate Dense and Sparse Representations for Zero-Shot Document Retrieval - ielab/PromptReps
            
                
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             (5) and finally, this is work in progress: we have new experiments running and we plan to roll out iterative updates to results as we get them finished and written up. so, stay tuned! 
          
                
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             This was possible thanks to @CSIRO_News new Virga GPU compute facility, that boasts 448 H100s. This is a great commitment to AI and in particular LLM research by CSIRO. It also highlights the need for a national GPU infra to foster research at Australian universities 
          
                
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             Our new work "PromptReps: Prompting Large Language Models to Generate Dense and Sparse Representations for Zero-Shot Document Retrieval" (@ShengyaoZhuang @xueguang_ma @bevan_koopman @lintool @guidozuc)  https://t.co/qNfj48gbEx  a ๐งต 
          
            
            arxiv.org
              Utilizing large language models (LLMs) for zero-shot document ranking is done in one of two ways: (1) prompt-based re-ranking methods, which require no further training but are only feasible for...
            
                
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             (1 -- perhaps the most trivial) this is the first work in Information Retrieval that reports results on Llama3, including the 70B model: and this was achieved within 10 days of model release. 
          
                
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             This paper is receiving good attention, also featuring on the May 2024 Trends in AI by @ZetaVector. I am excited about this work, for several reasons. Here they come... 
          
                
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             ๐ Excited to share that our abstract "Incorporating Changes in Review Outcomes in the Evaluation of Systematic Review Automation" has been accepted for a short oral presentation at the Global Evidence Summit @GESummit 2024. Work done with @allanhanbury @petrknoth @guidozuc ๐ 
          
                
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             Our review describes the different types of LLM, their emerging applications and potential limitations and bias and likely future translation into clinical practice 
          
                
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             "The new paradigm in machine learning โ foundation models, large language models and beyond: a primer for physicians" by Ian Scott & I (@guidozuc) is now available in Internal Medicine Journal: 
          
            
            onlinelibrary.wiley.com
              Foundation machine learning models are deep learning models capable of performing many different tasks using different data modalities such as text, audio, images and video. They represent a major...
            
                
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             now at #EMNLP2023 @bevan_koopman is presenting our paper "Dr ChatGPT tell me what I want to hear: How different prompts impact health answer correctness"  https://t.co/t6rzC7vVI7  Apparently the first Human-Centered NLP session at an NLP conference (so said the session chair) 
          
                
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             Katya Khramtsova presenting our paper "Selecting which Dense Retriever to use for Zero-Shot Search" @SIGIR_AP #SIGIR_AP2023: can we select which dense retriever to use on your new dataset, without needing labels for evaluation? w @ShengyaoZhuang @guidozuc
             https://t.co/pHdtBDZJjX 
          
          
                
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