Search: “llm”

This r/MachineLearning discussion thread addresses the common and frustrating experience of receiving highly polarizing reviewer scores for ICML paper submissions — for example, one reviewer rating a

Harrison Chase, co-founder and CEO of LangChain, made a post on X affirming a point about where value lies in AI systems, specifically arguing that value is found 'in the harness' — referring to the s

This one gives a lot of perspective over the fact that memory isn't just a plugin anymore. My take is, each approach has it's tradeoffs but for me the mental model is, if the memory is more than or 80

Harrison Chase (creator of LangChain) shared a concise architectural principle regarding AI agent design: memory and harness components should remain on the application side of the API boundary rather

very memgpt / sarah wooders coded. memory isn’t a layer, it is the system. most teams think they’re choosing a model, but they’re really choosing where their memory lives and like ben thompson says, o

This Reddit post from r/ollama showcases a demonstration of running Kimi AI agents — powered locally via Ollama — within a platform called CopeAi.net, which appears to integrate AI agents with the Eth

without memory, ux with an agent is really bad memory is what makes an experience with an agent feel personal and optimized i'm doing a bunch of research re how folks are building memory into their ag

**llama.cpp release b8753** is a specific tagged build of the [llama.cpp](https://github.com/ggml-org/llama.cpp) project by ggml-org, an open-source C/C++ framework for running large language model...

The search results did not return the specific changelog details for build b8756. Based on what is available and the general context of llama.cpp's rolling release model, here is a factual summary ...

Chiasmus (reversing grammatical structures in two sentences for drama). Asyndetic tricolon (three items listed without a conjunction). Parataxis (short and somewhat disconnected dramatic sentences). S

@hwchase17 Agent harnesess will simplify multi-agent orchestration and it is finally the next big thing, albeit it looks different from what we had imagined 3 year ago (AutoGen & CrewAI), 2 year ago (

@hwchase17 @sarahwooders like a the old children's school flipbook - each one wakes up, takes in the context(memory) via harness does its thing, then rests.... next flip book page, the harness manages

A developer shared an open-source Android keyboard on r/ollama that integrates local AI capabilities by connecting to self-hosted inference servers such as Ollama, LM Studio, or any OpenAI-compatible

The specific Reddit thread could not be retrieved directly, but based on its title, source, and the broader context of r/MachineLearning discussions, here is a fitting knowledge base summary: This r/M

Most illuminating graph I have seen for definition of harness. Memory and context are deeply coupled with harness. In my humble opinion, how they are injected and managed are one of most important pie

Users running OpenClaw with `gemma4:26b` via Ollama encounter significantly slow or timed-out first turns in a session, even though the model responds quickly when queried directly through raw Olla...

The most important post I've read all week by @hwchase17 . Memory, particularly memory consistency is the biggest performance inhibitor to AI agents today. As we interact with different harnesses and

This is the right frame. We’re currently designing our agent memory platform, and the hardest part isn’t storage — it’s deciding what to remember, when to retrieve, and how to keep context clean. All

What if owning the memory layer goes far beyond escaping lock-in? What if memory becomes fully editable intelligence? You could debug bad patterns, reinforce good ones, and crucially synthesize new on

A Reddit discussion from the r/ollama community where a user seeks advice on which AI language model to run locally using Ollama. Responses likely include hardware-based recommendations (such as RAM a

arXiv:2604.06227v1 Announce Type: new Abstract: Accurate short-term forecasting of agricultural commodity prices is critical for food security planning and smallholder income stabilisation in developi

Apple is presenting new research at the ACM CHI Conference on Human Factors in Computing Systems, held in person in Barcelona, Spain, from April 13–17, 2026, and is a sponsor of the event. Research...

arXiv:2604.07615v1 Announce Type: new Abstract: In language model interpretability research, extbf{circuit tracing} aims to identify which internal features causally contributed to a particular outp

arXiv:2604.08077v1 Announce Type: new Abstract: Processing long-form videos with Video Large Language Models (Video-LLMs) is computationally prohibitive. Current efficiency methods often compromise fi

arXiv:2604.08525v1 Announce Type: cross Abstract: Today's large language models (LLMs) are trained to align with user preferences through methods such as reinforcement learning. Yet models are beginni

arXiv:2306.02781v4 Announce Type: replace-cross Abstract: Generative artificial intelligence, and large language models in particular, have emerged as one of the most transformative paradigms in moder

arXiv:2604.07755v1 Announce Type: new Abstract: Despite extensive research, Large Language Models continue to hallucinate when generating code, particularly when using libraries. On NL-to-code benchma

**deepagents** (github.com/langchain-ai/deepagents) is an open-source, MIT-licensed agent harness built on LangChain and LangGraph, equipped with built-in task planning, a filesystem backend, subag...

As agent systems scale, the control layer becomes the main source of complexity. What starts simple turns into coordination and composition problems. I built langchain-middleware-stack to better struc

arXiv:2604.06266v1 Announce Type: cross Abstract: Software-Defined Networking (SDN) improves network flexibility but also increases the need for reliable and interpretable intrusion detection. Large L

arXiv:2505.20662v3 Announce Type: replace Abstract: Efficient reproduction of research papers is pivotal to accelerating scientific progress. However, the increasing complexity of proposed methods oft

The search results do not contain the specific changelog details for llama.cpp release **b8748**. The closest available data is for build b8747 (the latest at time of search), and no per-build note...

The search results do not contain specific changelog details for the exact `b8749` tag. Based on the available information about the llama.cpp project and its release cadence, here is a factual sum...

**llama.cpp release b8750** is a tagged build of [llama.cpp](https://github.com/ggml-org/llama.cpp), the open-source C/C++ inference engine for large language models maintained under the ggml-org G...

arXiv:2508.04691v2 Announce Type: replace-cross Abstract: As humans move toward collaborating with coordinated robot teams, understanding how these teams coordinate and fail is essential for building

arXiv:2604.06674v1 Announce Type: cross Abstract: Meaning in Persian poetry is both historical and relational. Words persist through literary tradition while shifting their force through changing cons

arXiv:2604.07606v1 Announce Type: new Abstract: AI-driven sign language interpretation is limited by a lack of high-quality annotated data. New datasets including ASL STEM Wiki and FLEURS-ASL contain

arXiv:2604.06212v1 Announce Type: cross Abstract: Analytical code is essential for reproducing diagnostic and prognostic prediction model research, yet code availability in the published literature re

arXiv:2604.07484v1 Announce Type: cross Abstract: Generative reward models (GRMs) have emerged as a promising approach for aligning Large Language Models (LLMs) with human preferences by offering grea

In support of our mission to accelerate the developer journey on Google Cloud, we built Dev Signal: a multi-agent system designed to transform raw community signals into reliable technical guidance by

arXiv:2512.19173v2 Announce Type: replace Abstract: Current chart-related tasks, such as chart generation (NL2Chart), chart schema parsing, chart data parsing, and chart question answering (ChartQA),

A bug was identified in NVIDIA's cuBLAS library where `cublasSgemmStridedBatched` dispatches the same suboptimal `cutlass_80_simt_sgemm_128x32_8x5` kernel for every batched FP32 workload from 256×...

arXiv:2601.05524v2 Announce Type: replace Abstract: Parallel Speculative Decoding (PSD) accelerates traditional Speculative Decoding (SD) by overlapping draft generation with verification. However, it

arXiv:2604.07003v1 Announce Type: new Abstract: Large language models (LLMs) has been widely used for automated negotiation, but their high computational cost and privacy risks limit deployment in pri

arXiv:2604.06826v1 Announce Type: cross Abstract: Environmental, Social, and Governance (ESG) considerations are increasingly integral to assessing corporate performance, reputation, and long-term sus

arXiv:2604.06370v1 Announce Type: cross Abstract: The serving paradigm of large language models (LLMs) is rapidly shifting towards complex multi-agent workflows where specialized agents collaborate ov