Pace
PulseAugur coverage of Pace — every cluster mentioning Pace across labs, papers, and developer communities, ranked by signal.
- developed by Gotit.pub 90%
- developed alphaXiv 90%
- developed ScienceCast 90%
- developed by ScienceCast 90%
- developed Gotit.pub 90%
- developed by alphaXiv 90%
- developed CatalyzeX 90%
- developed scite Smart Citations 90%
- developed by scite Smart Citations 90%
- developed CORE Recommender 90%
- developed by CORE Recommender 90%
- instance of Gotit.pub 70%
- 2026-09-10 research_milestone Researchers introduced PACE, a backpropagation-free continual test-time adaptation system that achieves state-of-the-art accuracy and reduces runtime by over 50%. source
- 2026-07-13 research_milestone Researchers introduced PACE, an AI system for personalized 9-1-1 call-taker training, demonstrating significant improvements in training efficiency and mastery. source
- 2026-05-27 funding NYC-based Pace, an AI company automating insurance operations, raised $46 million in Series B funding led by Thrive and Sequoia at a $375 million valuation. source
- 2026-05-27 funding Pace raised $46 million in Series B funding co-led by Thrive Capital and Sequoia Capital, valuing the company at $375 million. source
- 2026-05-25 research_milestone A new research paper introduces the PACE framework for self-evolving small language model agents. source
6 day(s) with sentiment data
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New LLM serving technique boosts efficiency; CPU benchmarks show Gemma3:4b excels
A new paper introduces PACE, a system designed to improve the efficiency of Large Language Model (LLM) serving by optimizing the handling of parallel branches in requests. Unlike existing methods that either admit branc…
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New diagnostic tool PACE predicts human-gain curves in AI optimization
Researchers have developed PACE (Proxy Alignment and Curvature Expansion), a new diagnostic tool designed to predict how human-perceived quality will change as optimization strength increases. Unlike previous methods th…
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New PACE framework compresses native MLLMs with over 2x FLOPs reduction
Researchers have developed PACE, a novel compression framework specifically designed for native multimodal large language models (native MLLMs). Unlike previous methods that targeted ViT-based models, PACE addresses the…
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New agent PACE aids adaptive conjecture exploration in applied mathematics
Researchers have developed PACE, a novel agent designed for adaptive conjecture exploration in applied mathematics. PACE operates through a structured research loop, enabling it to select mathematical objectives and dev…
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New PACE framework improves streaming video understanding response timing
Researchers have developed PACE, a novel training-free framework for improving response timing in streaming video understanding. PACE addresses three key error patterns: answer instability, lack of grounding in observed…
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Video unlearning privacy leaks stem from redundancy, not trajectory
Researchers have identified that cross-frame redundancy, rather than object trajectory, is the primary source of privacy leakage in video unlearning models. Current evaluation methods, which analyze frames individually,…
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New PACE quantizer slashes memory for four-bit recurrent states
Researchers have developed PACE, a novel post-hoc quantizer for four-bit recurrent states in linear-attention language models. PACE reduces the frequency of state rounding and employs column-wise quantization scales to …
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New PACE method enhances AI multimodal reasoning with Qwen3-VL-8B-Instruct
Researchers have developed a new method called PACE (Pairwise Token Contrast and Adaptive Trajectory Confidence) to improve multimodal reasoning in AI models. PACE addresses limitations in existing methods by analyzing …
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New benchmark and method for unlearning LLM personas introduced
Researchers have introduced PersonaUnlearnBench, a new benchmark designed to evaluate the effectiveness of unlearning specific personas from large language models (LLMs). The benchmark, which covers six LLMs and five di…
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New PACE system precisely grounds AI-generated film previsualization
Researchers have introduced PACE (Precise AI Cinematic Expression), a new typed representation system designed to bridge the gap between screenplays and film previsualization. PACE allows for detailed, hierarchical decl…
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AI Researchers Demand Pace of AI Development Amid Safety Concerns · 2 sources tracked
A group of prominent AI researchers, including Geoffrey Hinton and Yoshua Bengio, are calling for a pause or slowdown in the development of advanced AI systems. They cite concerns about the potential risks and existenti…
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New PACE framework enhances multimodal embedding models
Researchers have developed PACE, a novel two-stage framework designed to improve multimodal embedding models. This framework addresses the limitations of existing cosine-based contrastive objectives by progressively exp…
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New PACE framework slashes dialogue serving latency and filler conflicts
Researchers have developed PACE, a framework designed to improve the efficiency and quality of retrieval-augmented dialogue systems. PACE formalizes Perceived Time-to-First-Response (PTFR) as a key objective and uses a …
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New PACE system optimizes AI adaptation with 50% runtime reduction
Researchers have developed PACE, a new system for backpropagation-free continual test-time adaptation that optimizes normalization layer parameters. This method uses the Covariance Matrix Adaptation Evolution Strategy w…
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New PACE method enhances robot sim-to-real transfer using proprioception
Researchers have developed a new method called PACE (Proprioception-Anchored Cross-Modal Encoder) to improve the transfer of reinforcement learning policies from simulation to real-world robotics tasks. PACE leverages p…
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New PACE method enhances personalized federated graph learning
Researchers have developed PACE, a novel method for personalized federated graph learning that addresses client heterogeneity. PACE treats collaborative knowledge as a compact correction to a local model rather than a r…
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New dataset PACE and PaceMaker framework tackle hidden conflicts in AI assistants
Researchers have introduced PACE, a new dataset designed to evaluate personalized AI assistants' ability to identify hidden conflicts between user requests and contextual information. Existing models struggle with this …
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Insurance adjusters express strong negative sentiment towards AI integration · 5 sources tracked
Insurance claims adjusters are expressing significant dissatisfaction with the increasing integration of AI into their profession. Many view AI tools as error-prone and burdensome, leading to misclassified claims and in…
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New agentic framework automates publisher-specific content extraction for LLMs
Researchers have developed PACE, an agentic framework designed to automate the extraction of publisher-specific content for LLM data pipelines. PACE learns extraction configurations from sample pages and user requiremen…
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PACE framework accelerates VLM inference by optimizing vision encoder and LLM
Researchers have introduced PACE, a novel training-free framework designed to accelerate the inference speed of Vision-Language Models (VLMs). PACE addresses limitations in existing methods by optimizing both the vision…