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nd learning 1 experimental design 1 f fact verification 5 few shot learning 12 firecracker 5 formal verification 2 g generative adversarial networks gans 2 generative ai 6 graph neural networks gnns 12 h homomorphic encryption 1 human robot interaction 2 hyperbolic embedding 2 hyperparameter optimization 4 i image classification 2 k knowledge discovery 2 knowledge distillation 2 knowledge graphs 5 l language models 15 large language models llms 19 learning algorithms 1 learning to rank 2 m machine translation 6 meta learning 2 multilingual 4 multimodal interaction 6 multitask learning 4 n natural language generation 2 natural language processing nlp 10 natural language understanding nlu 44 network architectures 1 neural machine translation 4 neural networks 7 nsdi 5 o object detection 4 p paralinguistics 1 parameter estimation optimization 2 prime video 1 privacy preserving machine learning 2 q quantum computing 1 question answering 28 r reasoning 3 recommender systems 3 regression 2 reinforcement learning 6 responsible ai 8 s search 1 self supervised learning 5 semi supervised learning 5 signal processing 1 speech 2 speech enhancement 1 spoken language understanding slu 1 stochastic models 1 synthetic data generation 2 t text classification 2 text mining 3 text normalization 1 text summarization 7 text to speech tts 1 time series 6 transfer learning 2 truth and trust online 4 u unsupervised learning 4 v very large databases vldb 1 vision language models vlms 2 visual search 1 voice assistant 3 w weakly supervised learning 1 word embeddings 1 z zero shot learning 5 a b c d e f g h i j k l m n o p q r s t u v w x y z apply author saab mansour 15 bing xiang 13 dilek hakkani tür 13 dan roth 11 george karypis 10 mu li 10 ramesh nallapati 10 stefano soatto 10 karthik gopalakrishnan 8 yi zhu 8 see all author a alessandro achille 3 alessandro moschitti 7 alex smola 5 alexandros papangelis 3 amir saffari 3 amol lele 3 andreas vlachos 4 andrew o arnold 5 anjali narayan chen 3 anna currey 3 anoop deoras 4 arpit mittal 5 arshit gupta 3 avinash ravichandran 6 b behnam hedayatnia 6 bing shuai 4 bing xiang 13 c charith peris 4 christos christodoulopoulos 7 cicero nogueira dos santos 4 cédric archambeau 4 d da zheng 5 dan roth 11 daniele bonadiman 4 danielle maddix robinson 4 davide bernardi 4 davide modolo 3 dejiao zhang 5 dilek hakkani tür 13 dominik janzing 3 e ehsan m kermani 7 f feng nan 5 g george karypis 10 georgiana dinu 3 gokhan tur 7 govind thattai 4 h haidar khan 3 hang su 5 hao chen 3 henghui zhu 5 hwanjun song 4 i igor shalyminov 5 j jack g m fitzgerald 6 james thorne 4 jason krone 6 joe tighe 5 julian salazar 3 k karthik gopalakrishnan 8 kathleen mckeown 6 katrin kirchhoff 4 kevin small 3 konstantine arkoudas 5 l lorenzo stella 3 luca soldaini 3 m marcello federico 4 markus dreyer 3 mohit bansal 4 mu li 10 n nikhil rao 3 nikhil yogendra murali 4 p parminder bhatia 3 peter gehler 3 prashant mathur 5 pratik chaudhari 4 prem natarajan 4 q qiaozi qz gao 3 r rahul gupta 3 ramesh nallapati 10 rashmi gangadharaiah 4 rasool fakoor 5 s saab mansour 15 seokhwan kim 4 sergul aydore 3 shuai zheng 3 siffi singh 5 soji adeshina 4 sravan bodapati 3 stefano soatto 10 t thomas brox 4 v vandana kannan 3 varun kumar 4 w wael hamza 4 wei xia 3 wei xiao 4 x xiang song 4 xiaofei ma 6 xinyu li 5 y yang liu 5 yassine benajiba 4 yi zhang 7 yi zhu 8 yida wang 3 yogarshi vyas 3 yoshitomo matsubara 3 yuyang bernie wang 4 z zheng li 3 zheng zhang 5 zhi zhang 4 zhiguo wang 3 zhiheng huang 3 a b c d e f g h i j k l m n o p q r s t u v w x y z apply year 2026 1 2025 11 2024 24 2023 40 2022 82 2021 60 2020 38 2019 14 2018 13 2017 2 2016 1 286 results found sort relevance newest oldest a z z a gpt oss java inference xu zhang 2026 a pure java implementation of openai s gpt oss inference in 1000 lines of code optimized for cpu execution inspired by llama cpp llama2 c this repo ports the gpt oss pytorch model py to efficient java code emphasizing minimalism simplicity and educational purpose key features pure java no native dependencies runs anywhere with java 23 complete gpt oss architecture full implementation of moe machine learning tiser adrian bazaga rexhina blloshmi bill byrne adrià de gispert 2025 tiser incorporates a multi stage inference pipeline that combines explicit reasoning timeline construction and iterative self reflection the key idea behind our approach is to empower llms to adapt by scaling their internal reasoning process during inference tiser enables models to systematically organize temporal information verify their inferences and refine their outputs conversational ai codeassistbench myeongsoo kim shweta garg baishakhi ray varun kumar anoop deoras 2025 codeassistbench provides a complete framework for evaluating ai coding assistants through multi agent workflows docker validation and comprehensive metrics collection built for researchers ml engineers and developers who need robust reproducible evaluation of code generation agents machine learning icecream identifying coalition based explanations for common and rare events in any model michael oesterle patrick blöbaum atalanti mastakouri elke kirschbaum 2025 which set of features was responsible for a certain output of a machine learning model which components caused the failure of a cloud computing application these are just two examples of questions we are addressing in this work by identifying coalition based explanations for common and rare events in any model icecream specifically we propose an information theoretic quantitative measure for the influence machine learning agentoccam ke yang yao liu sapana chaudhary rasool fakoor pratik chaudhari george karypis huzefa rangwala 2025 agentoccam offers a simple but strong baseline for llm based web agents by providing a url and the task you want it to perform agentoccam can execute it for you its simplicity and effectiveness allow you to run it directly or adapt it into a larger pipeline for its executing web tasks such as web information retrieval before processing the documents without using in context examples new agent roles enhancing language model agents using diversity of thoughts vijay lingam behrooz omidvar tehrani sujay sanghavi gaurav gupta sayan ghosh linbo liu luke huan anoop deoras 2025 a popular approach to building agents using language models lms involves iteratively prompting the lm reflecting on its outputs and updating the input prompts until the desired task is achieved however our analysis reveals two key shortcomings in the existing methods i limited exploration of the decision space due to repetitive reflections which result in redundant inputs and ii an inability machine learning beyondcorrelation the impact of human uncertainty in measuring the effectiveness of automatic evaluation and llm as a judge aparna elangovan lei xu jongwoo ko mahsa elyasi ling liu sravan bodapati dan roth 2025 the effectiveness of automatic evaluation of generative models is typically measured by comparing the labels generated via automation with human labels using correlation metrics however metrics like krippendorff s α and randolph s κ were originally designed to measure the reliability of human labeling thus make assumptions about typical human labeling behavior and these assumptions may not be applicable conversational ai open domain question answering with conflicting contexts siyi liu qiang ning kishaloy halder wei xiao zheng qi phu mon htut yi zhang neha anna john bonan min yassine benajiba dan roth 2025 open domain question answering systems frequently rely on information retrieved from large collections of text such as the web to answer questions however such collections of text often contain conflicting information and indiscriminately depending on this information may result in untruthful and inaccurate answers to understand the gravity of this problem we collect a human annotated dataset question conversational ai eci sampling gradient free generation for hard constrained systems chaoran cheng boran han danielle maddix robinson abdul fatir ansari andrew stuart michael mahoney yuyang bernie wang 2025 we present eci sampling stands for extrapolation correction interpolation as a novel framework for adapting pre trained unconstrained generative models to exactly satisfy constraints in a zero shot manner without requiring expensive gradient computations or fine tuning machine learning spectro riemannian graph neural networks karish grover haiyang yu xiang song qi zhu han xie vassilis n ioannidis christos faloutsos 2025 can integrating spectral and curvature signals unlock new potential in graph representation learning non euclidean geometries particularly riemannian manifolds such as hyperbolic negative curvature and spherical positive curvature offer powerful inductive biases for embedding complex graph structures like scale free hierarchical and cyclic patterns meanwhile spectral filtering excels at processing machine learning cdsl nishanth sridhar nakshatri shamik roy rajarshi raj das un ch leo boytsov rashmi gangadharaiah 2025 this repository will contain the official implementation of the naacl 2025 paper constrained decoding with speculative lookaheads conversational ai pixels progressive image xemplar based editing with latent surgery shristi das biswas matthew shreve xuelu li prateek singhal kaushik roychoudhury roy 2025 recent advancements in language guided diffusion models for image editing are often bottle necked by cumbersome prompt engineering to precisely articulate desired changes an intuitive alternative calls on guidance from in the wild image exemplars to help users bring their imagined edits to life contemporary exemplar based editing methods shy away from leveraging the rich latent space learnt by pre existing computer vision 1 2 3 24 next more resources amazon science github explore open source code and datasets from amazon s science community aws open source aws is proud to support open source projects foundations and partners aws open data browse available data and learn how to register your own datasets related content see more see more amazon and university of michigan give robots a sense of touch mani nambi nima fazeli july 10 2026 hydroshear a new physics based simulator teaches robots how to use their sense of touch to perform complex manipulation tasks in a way that transfers seamlessly to the real world robotics capturing token ids during agentic interactions for better reinforcement learning frederick robinson july 9 2026 a new rust proxy called turnstile sits between the model backend and the agent harness to capture information lost in mere text transcripts machine learning novel kaputt dataset sets new benchmark for large scale visual defect detection sebastian hoefer october 2 2025 a new dataset with over 238 000 images challenges and advances the state of the art in visual defect detection for complex retail applications computer vision work with us see more jobs see more jobs applied science manager personalization il tel aviv are you a scientist interested in pushing the state of the art in information retrieval large language models and recommendation systems are you interested in innovating on behalf of millions of customers helping them accomplish their every day goals do you wish you had access to large datasets and tremendous computational resources do you want to join a team of capable scientist and engineers building the future of e commerce answer yes to any of these questions and you will be a great fit for our team at amazon our team is part of amazon s personalization organization a high performing group that leverages amazon s expertise in machine learning generative ai large scale data systems and user experience design to deliver the best shopping experiences for our customers our team is building next generation personalization systems powered by large language models we are tackling novel research challenges to help customers discover products they ll love at amazon scale and latency requirements we are a team uniquely placed within amazon to have a direct window of opportunity to influence how customers will think about their shopping journey in the future as an applied science manager you will lead a team of scientists working at the frontier of llm based personalization you will set the technical vision drive the research agenda and ensure your team delivers production ready solutions you will hire mentor and develop world class scientists while fostering a culture of innovation and scientific rigor you will partner closely with engineering and product teams to translate ambitious research into customer facing impact and represent your team s work to senior leadership please visit https www amazon science for more information data scientist iii amazon 1p credito payments br sp sao paulo do you feel the challenge and the adrenaline kick when a huge data set stares you in the face and you know that somewhere inside are hidden very important business insights that can fundamentally alter the way top business leaders think and act do you enjoy presenting strong data backed insights to business leaders insights that can topple their long held beliefs and compel them to change their direction completely if yes then you are the one we are looking for we are looking to invite passionate leaders with expertise in generate power business insights from very large datasets on a journey where the primary aim would be to enable needle moving business impacts through statistical analysis we are looking for leaders who can envision the design and development of analytical infrastructure which can support strategic and tactical decision making those who join this high visibility team would have to navigate through significant ambiguity in defining business problems and converting them to analytical problems this role requires additional exposure and experience to machine learning key job responsibilities use machine learning and analytical techniques to create scalable solutions for business problems analyze and extract relevant information from large amounts of amazon s historical business data to help automate and optimize key processes design development evaluate and deploy innovative and highly scalable ml models such as risk scorecards income models fraud models for predictive learning in credit risk applications research and implement novel machine learning and statistical approaches work closely with software engineering teams to drive real time model implementations and new feature creations work closely with business owners and operations staff to optimize various business operations establish scalable efficient automated processes for large scale data analyses model development model validation and model implementation mentor other scientists and engineers in the use of ml techniques innovate with the latest genai technology to build highly automated solutions for e...