Heron is a passive network analyzer that reconstructs what your AI agents are actually doing. Zero SDKs. Zero proxy. Hook eBPF to see TLS-encrypted LLM calls and identify which agent process made them. Read more ›
Foundation decoders, a class of high-capacity neural decoders, are leading candidates for fault-tolerant quantum computing, with accurate and efficient decoding at large code distances. However, their construction often faces a steep scaling barrier, as larger code distances rapidly amplify the cost of syndrome generation and neural optimization. To address this bottleneck, here we devise neural transfer unification (NTU), a unified framework ... Read more ›
As autonomous agents tackle increasingly complex multi-step, multi-agent tasks, their execution trajectories have scaled beyond the constraints of even the largest context windows. Current methods for effectively diagnosing agent failures load the full trajectory into an LLM's context window, which suffers from attention dilution and fails when agentic traces inevitably exceed context limits. To address this, we introduce SAFARI (Scaling long-ho... Read more ›
Save up to $190 on your pass to TechCrunch Founder Summit 2026. Early Bird pricing ends today, at 11:59 p.m. PT, after which rates increase. Register now. Read more ›
<img src=" Interactions API is a unified interface for interacting with Gemini models and agents. Read more ›
Large language models (LLMs) exhibit strong capabilities in short-context reasoning but degrade in performance over long conversational horizons due to context window limitations and inefficient token usage. We introduce ContextForge, a system for context recycling that maintains task-relevant information across turns by combining structured query generation, external memory retrieval, and controlled synthesis. The system enables efficient reu... Read more ›
At present, more than 700 million people live with caloric hunger, and more than two billion suffer from micronutrient deficiencies, known as ‘hidden hunger’. From an agricultural viewpoint, three major objectives need to be worked towards simultaneously to achieve zero hunger (the United Nations Sustainable Development Goal 2): (1) enhanced yield; (2) higher vitamin and mineral density to sustain recommended daily intake (multi-biofortification); and (3) enhanced climate-change resilience. A... Read more ›
Open source authorization engine for AI agents. Confidence-aware gating · Human-in-the-loop review · Policy-as-code · Full audit trail - Lelu-ai/lelu Read more ›
Prototyper is the first visual workspace for your agents and your team. Give Claude Code, Codex, Cursor, and other agents a shared canvas for plans, apps, and diagrams. Read more ›
Complex multi-agent control tasks remain challenging for traditional rule-based and model-based approaches, motivating the adoption of learning-based methods. However, learning-based methods often struggle with sim-to-real transfer because they rely on accurate dynamics modeling or system identification and learn policies in low-level control spaces that are highly sensitive to dynamics mismatch, making them costly and fragile in complex envir... Read more ›
Intent-execution separation for LLM agents: the model emits typed intent (SIF) in a domain vocabulary; a deterministic layer validates, scopes, translates, and executes it. Java/Spring + Vue, with ... Read more ›
EEG foundation models can learn generalizable representations from large-scale EEG corpora to enable single-backbone transfer across diverse clinical and brain-computer interface tasks. Existing models typically discretize the continuous multi-channel EEG waveform into patches or codebook tokens and train a transformer with masked self-supervision. Recognizing that this discretization fragments continuous brain rhythms and obscures fine-graine... Read more ›
Low-bit floating-point formats and semi-structured sparsity are increasingly supported by modern accelerators, yet combining them for LLM activation compression remains challenging: activations contain input-dependent outliers that dominate block scales in FP4 quantization, and directly applying N:M sparsity masks discards moderate values, coupling sparsification loss with quantization error. We introduce SharQ, a training-free inference metho... Read more ›
The response of the nucleus of a deuterium atom to electric fields shows no evidence of asymmetry, which is consistent with conventional theories of particle physics. The response of the nucleus of a deuterium atom to electric fields shows no evidence of asymmetry, which is consistent with conventional theories of particle physics. Read more ›
MIT's 2026 AI and Society Forum featured research and panel discussions focused on AI and its impacts on democracy, politics, and the workplace of the present and the future. Read more ›
LLMs fine-tuned for security classification are usually evaluated on held-out examples from the same distribution as their training data. We show that this can miss vulnerabilities introduced by fine-tuning itself: models can learn token-level indicator semantics that preserve canonical accuracy while failing under behavior-preserving transformations such as PowerShell alias substitution, command reconstruction, string construction, execution ... Read more ›
Computer use agents (CUAs) have advanced rapidly in desktop automation, and a growing number of users deploy CUAs such as OpenClaw on Mac Mini for always-on automation. However, existing benchmarks, including those for macOS, evaluate agents without framework augmentation and rely on binary evaluation. As a result, they fail to capture both the framework capabilities leveraged by modern CUAs and the partial progress on long-horizon, multi-applic... Read more ›
Save up to $190 on your pass to TechCrunch Founder Summit 2026 by June 26, 11:59 p.m. PT. Designed for founders first on November 4 in Boston. Register here. Read more ›
This paper introduces a general methodology through which a population of autonomous agents can converge on a linguistic convention that enables them to refer to arbitrary entities in their environment. The linguistic convention emerges in a decentralised manner through local communicative interactions between pairs of agents drawn from the population. The emergent convention consists of associations between symbolic labels (word forms) and ... Read more ›