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1–80 of 2,317
- Aakanksha NaikAffiliation: Allen Institute for AI (AI2)Work: OLMo: Accelerating the Science of Language Models
- Aaron ParisiAffiliation: Google DeepMindWork: TALM: Tool Augmented Language Models
- Abhilasha RavichanderAffiliation: Max Planck Institute for Software Systems (MPI-SWS)Work: OLMo: Accelerating the Science of Language Models
- Adams Wei YuAffiliation: Google DeepMindWork: Finetuned Language Models Are Zero-Shot Learners
- Adil SalimAffiliation: Not recordedWork: Accelerating mathematical research with language models: A case study of an interaction with GPT-5-Pro on a convex analysis problem
- Aidan ClarkAffiliation: OpenAIWork: Training Compute-Optimal Large Language Models
- Aixin LiuAffiliation: Not recordedWork: DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models
- Alan AraziAffiliation: Prior LabsWork: Jamba: Hybrid Transformer-Mamba Language Models
- Alanna WaltonAffiliation: Not recordedWork: Gemma 2: Improving Open Language Models at a Practical Size
- Aleksandar BotevAffiliation: Not recordedWork: RecurrentGemma: Moving Past Transformers for Efficient Open Language Models
- Alex GuAffiliation: Not recordedWork: ProofOptimizer: Training Language Models to Simplify Proofs without Human Demonstrations
- Alex RayAffiliation: Pioneer Square LabsWork: Training language models to follow instructions with human feedback
- Alicia Vail ParrishAffiliation: Google DeepMindWork: Gemma 2: Improving Open Language Models at a Practical Size
- Alina OpreaAffiliation: Northeastern UniversityWork: Extracting Training Data from Large Language Models
- Alisa LiuAffiliation: OpenAIWork: SuperBPE: Space Travel for Language Models
- Allen HutchisonAffiliation: VycariWork: Gemma 2: Improving Open Language Models at a Practical Size
- Alon AlbalakAffiliation: Lila SciencesWork: Artificial Hivemind: The Open-Ended Homogeneity of Language Models (and Beyond)
- Amanda Carl-PrattAffiliation: Google DeepMindWork: Gemma 2: Improving Open Language Models at a Practical Size
- Amy ShenAffiliation: Not recordedWork: Saved link: Gemma 2: Improving Open Language Models at a Practical Size
- Anand RaoAffiliation: Not recordedWork: Gemma 2: Improving Open Language Models at a Practical Size
- Ananya Harsh JhaAffiliation: University of WashingtonWork: OLMo: Accelerating the Science of Language Models
- Ananya KumarAffiliation: MetaWork: Holistic Evaluation of Language Models
- Anca DraganAffiliation: Google DeepMindWork: Gemma 2: Improving Open Language Models at a Practical Size
- Andrew N. CarrAffiliation: Cartwheel Inc. (Cartwheel)Work: Evaluating Large Language Models Trained on Code
- Andy BrockAffiliation: Not recordedWork: Saved link: Gemma 2: Improving Open Language Models at a Practical Size
- Andy CoenenAffiliation: Google DeepMindWork: Gemma 2: Improving Open Language Models at a Practical Size
- Anthony LaforgeAffiliation: GoogleWork: Gemma 2: Improving Open Language Models at a Practical Size
- Ariel Herbert-VossAffiliation: RunSybilWork: Language Models are Few-Shot Learners
- Arman CohanAffiliation: Yale UniversityWork: OLMo: Accelerating the Science of Language Models
- Armand JoulinAffiliation: Google DeepMindWork: LLaMA: Open and Efficient Foundation Language Models
- Aurelia GuyAffiliation: Not recordedWork: Training Compute-Optimal Large Language Models
- Aurélien RodriguezAffiliation: CohereWork: LLaMA: Open and Efficient Foundation Language Models
- Aviral KumarAffiliation: Carnegie Mellon University, School of Computer ScienceWork: Training Language Models to Self-Correct via Reinforcement Learning
- Baptiste RozièreAffiliation: Mistral AIWork: LLaMA: Open and Efficient Foundation Language Models
- Barak PelegAffiliation: AI21 LabsWork: Jamba: Hybrid Transformer-Mamba Language Models
- Behnam NeyshaburAffiliation: MirendilWork: Gemma 2: Improving Open Language Models at a Practical Size
- Bei FengAffiliation: Not recordedWork: DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models
- Beidi ChenAffiliation: Carnegie Mellon UniversityWork: Efficient Streaming Language Models with Attention Sinks
- Ben AviramAffiliation: Not recordedWork: Jamba: Hybrid Transformer-Mamba Language Models
- Ben BastianAffiliation: GoogleWork: Gemma 2: Improving Open Language Models at a Practical Size
- Benjamin NewmanAffiliation: University of WashingtonWork: ArxivDIGESTables: Synthesizing Scientific Literature into Tables using Language Models
- Brandon RoyalAffiliation: Google CloudWork: Gemma 2: Improving Open Language Models at a Practical Size
- Brian IchterAffiliation: Physical IntelligenceWork: Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
- Brian LesterAffiliation: Google DeepMindWork: Finetuned Language Models Are Zero-Shot Learners
- Bryan CatanzaroAffiliation: NVIDIAWork: Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism
- Can XuAffiliation: Not recordedWork: WizardLM: Empowering large pre-trained language models to follow complex instructions
- Carlos E. JimenezAffiliation: Not recordedWork: SWE-bench: Can Language Models Resolve Real-World GitHub Issues?
- Carroll L. WainwrightAffiliation: Not recordedWork: Saved link: Training language models to follow instructions with human feedback
- Carroll WainwrightAffiliation: MetaculusWork: Training language models to follow instructions with human feedback
- Ce ZhangAffiliation: University of Chicago; Together AI; INSAITWork: Holistic Evaluation of Language Models (HELM)
- Chen AlmagorAffiliation: AI21 LabsWork: Jamba: Hybrid Transformer-Mamba Language Models
- Chen ElkindAffiliation: Google ResearchWork: TrueTeacher: Learning Factual Consistency Evaluation with Large Language Models
- Chenel ElkindAffiliation: Google ResearchWork: TrueTeacher: Learning Factual Consistency Evaluation with Large Language Models
- Chong ZhangAffiliation: OpenAIWork: Training language models to follow instructions with human feedback
- Chris PerryAffiliation: VycariWork: Gemma 2: Improving Open Language Models at a Practical Size
- Chris WeltyAffiliation: GoogleWork: Gemma 2: Improving Open Language Models at a Practical Size
- Christian CosgroveAffiliation: Not recordedWork: Holistic Evaluation of Language Models
- Christopher BernerAffiliation: Not recordedWork: Language Models are Few-Shot Learners
- Chunming HeAffiliation: Duke UniversityWork: Awesome Multimodal Large Language Models In Low-level Vision
- Claire CuiAffiliation: GoogleWork: GLaM: Efficient Scaling of Language Models with Mixture-of-Experts
- Clemens WinterAffiliation: OpenAIWork: Language Models are Few-Shot Learners
- Crystal NamAffiliation: Allen Institute for Artificial Intelligence (Ai2)Work: OLMo: Accelerating the Science of Language Models
- Dale SchuurmansAffiliation: Google DeepMind; University of AlbertaWork: Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
- Damai DaiAffiliation: DeepSeek-AIWork: Conditional Memory via Scalable Lookup: A New Axis of Sparsity for Large Language Models
- Daniel GissinAffiliation: AI21 LabsWork: Jamba: Hybrid Transformer-Mamba Language Models
- Daniel Jannai-EpsteinAffiliation: Not recordedWork: Jamba: Hybrid Transformer-Mamba Language Models
- Daniel KhashabiAffiliation: Johns Hopkins University, Department of Computer ScienceWork: Self-Instruct: Aligning Language Models with Self-Generated Instructions
- Daniel M. ZieglerAffiliation: Not recordedWork: Fine-Tuning Language Models from Human Preferences
- Daniel Voigt GodoyAffiliation: Linux Foundation and Data Science RetreatWork: A Hands-On Guide to Fine-Tuning Large Language Models with PyTorch and Hugging Face
- Danish ContractorAffiliation: IBM ResearchWork: Reducing the Scope of Language Models
- Dasha ValterAffiliation: BioptimusWork: Scaling Instruction-Finetuned Language Models
- Dave CummingsAffiliation: OpenAIWork: Evaluating Large Language Models Trained on Code
- David AtkinsonAffiliation: Future of Life InstituteWork: OLMo: Accelerating the Science of Language Models
- David WeinbergerAffiliation: Harvard UniversityWork: Gemma 2: Improving Open Language Models at a Practical Size
- Deepak NarayananAffiliation: NVIDIAWork: Holistic Evaluation of Language Models
- Denny ZhouAffiliation: MetaWork: Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
- Dian YuAffiliation: Not recordedWork: ReAct: Synergizing Reasoning and Acting in Language Models
- Dilara SoyluAffiliation: Stanford UniversityWork: Holistic Evaluation of Language Models
- Dimitris TsiprasAffiliation: OpenAIWork: Holistic Evaluation of Language Models
- Dimple VijaykumarAffiliation: Google DeepMindWork: Gemma 2: Improving Open Language Models at a Practical Size