Tag
PhotoCraft proposes a training-free hierarchical memory system for photo-search agents, integrating working, episodic, and semantic memory to maintain long-horizon context and transfer knowledge across tasks, achieving up to 18.5% improvement on DISBench.
LaSR proposes a latent reasoning training paradigm for context-aware speech recognition, aligning chain-of-thought supervision around acoustic features to improve terminology recognition without added latency, outperforming standard fine-tuning on Fun-Audio-Chat.
Spice is an open-source runtime that acts as a decision layer above AI agents, observing context, simulating options, and dispatching tasks to agents before execution.
This paper introduces a knowledge-based approach using knowledge graph embeddings to automatically assess big data quality by predicting missing edges between context representations and quality rules, outperforming traditional matching methods.
Google's Nexus paper proposes an agentic framework that incorporates contextual events alongside numerical data for time series forecasting, achieving an 86.6% MAPE reduction on Zillow tests compared to direct chain-of-thought prompting.
Coworker AI offers context-aware model routing to reduce AI spending while maintaining performance.
Tabracadabra has been upgraded to a context-aware assistant for any textbox, eliminating the need to switch between chat interfaces. It is now open-sourced.
Proposes AR-VLA, an autoregressive action expert that generates continuous action sequences with long-term memory for context-aware robotic policy training, improving trajectory smoothness and task success rates over reactive VLA models.
A research paper proposing NWCAD (No-Worse Context-Aware Decoding), a decode-time adapter that prevents 'neutral regression' where LLMs overwrite already-correct answers when given non-informative context, using a two-stream architecture with gated fallback to no-context decoding.