Search: “llm”

arXiv:2607.12051v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly being explored for clinical decision support, but their reliability in complex oncology treatment planning

arXiv:2607.07652v1 Announce Type: cross Abstract: Search engines have long allocated attention on the web by routing users from queries to websites. AI search changes this arrangement because informat

arXiv:2607.12058v1 Announce Type: cross Abstract: Given a vulnerability-fixing commit, trigger localization asks which specific statement turns the vulnerable program state into a concrete unsafe oper

arXiv:2607.12220v1 Announce Type: new Abstract: Synthesizing deployable robot behavior trees (BTs) from natural language (NL) requires grounding to ensure every generated BT references only skills a r

arXiv:2607.12962v1 Announce Type: cross Abstract: Frozen small code LLMs are deployed locally, yet the information guiding a retry after a failed attempt is still measured without placebo controls in

arXiv:2607.09224v2 Announce Type: replace-cross Abstract: Version control systems are essential for collaborative software development, yet tools like git remain challenging for many practitioners. Re

Hey r/LocalLLaMA — solo researcher here. I built a new attention architecture and want independent testers. Wave Field LLM replaces O(N²) dot-product attention with FFT wave convolution on a field. Tr

arXiv:2607.12713v1 Announce Type: cross Abstract: Generated tokens are a direct driver of the cost, latency, and energy of generative AI (GAI) code editing. We show the format of feedback is a lever o

arXiv:2607.12085v1 Announce Type: new Abstract: Evaluating retail conversational agents requires methods beyond lexical-overlap metrics to assess intent alignment, factuality, helpfulness, clarity, to

arXiv:2607.12246v1 Announce Type: new Abstract: Personalization in two-sided marketplaces relies heavily on user-level features, yet for platforms with infrequent, high-consideration purchases, a larg

arXiv:2607.11916v1 Announce Type: cross Abstract: The integration of Large Language Models (LLMs) with evolutionary computation has emerged as a powerful paradigm for automated heuristic design in com

arXiv:2607.11983v1 Announce Type: cross Abstract: A specialist tolerates blind spots that a generalist does not. Usually this is treated as a cost to be minimized. We treat it as a design variable: a

arXiv:2607.12395v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards without human-annotated data, often referred to as zero RL, has emerged as a powerful paradigm for elicit

arXiv:2607.12792v1 Announce Type: cross Abstract: Jailbreak-robustness research typically evaluates safety through generated responses using an LLM-as-judge approach. Such evaluations, however, are se

New work led by @FlemmingKondrup and @tomjiralerspong highlights an important vulnerability in chain-of-thought monitoring for agents, I highly recommend giving it a read. Link to the paper: https://a

The search did not return the specific details of the b9947 release. Based on the repository and context available: B9947 is a release of llama.cpp, which enables LLM inference in C/C++ . The release

b9950 is a release of llama.cpp, a C/C++ tool for LLM inference . This build number represents one of the frequent incremental releases from the llama.cpp project, which follows a rapid development cy

Release b9956 is a build version of llama.cpp, an open-source project for LLM inference in C/C++ . The project releases frequently, with multiple releases published in a single day , and b9956 represe

Release b9967 of llama.cpp, an LLM inference project in C/C++, includes an update to the server component allowing it to accept null sampling parameters (PR #25538). This change enables more flexible

arXiv:2607.08642v1 Announce Type: new Abstract: Speculative decoding accelerates LLM inference by drafting several tokens and verifying them in parallel. Block-diffusion drafters such as DFlash produc

arXiv:2607.07779v1 Announce Type: cross Abstract: Recent developments in AI for Mathematics (AI4Math), especially Large Language Model (LLM)-driven theorem provers, has achieved remarkable success in

arXiv:2607.08374v1 Announce Type: cross Abstract: Personality recognition has traditionally been constrained by theory-dependent formulations, where models are trained to fit predefined psychological

arXiv:2607.08180v1 Announce Type: cross Abstract: The rise of LLM-based agents with reasoning, summarization, and memory capabilities has created a new threat surface for online content that conventio

arXiv:2607.08681v1 Announce Type: new Abstract: As agentic AI systems are increasingly applied to cyber-physical environments, their evaluation requires assessment of both task performance and trustwo

arXiv:2607.08662v1 Announce Type: cross Abstract: Large language model (LLM)-based web search agents are transforming information seeking from simple factoid question answering into complex, deep-and-

arXiv:2607.08409v1 Announce Type: cross Abstract: LLM-based ASR adapted to regulated domains such as banking is bottlenecked by privacy: real speech is costly and legally constrained to collect, makin

b9935 is a build release from the llama.cpp project, which implements LLM inference in C/C++. The project doesn't follow traditional release practices, as multiple releases can be published in a singl

arXiv:2607.07696v1 Announce Type: cross Abstract: Analytical workloads operating on data stored in external database systems face a fundamental bottleneck: data access is guarded entirely by the datab

Character.AI's plan to become more than just an LLM-powered chatbot platform is going beyond interactive books, comics, and audio dramas. Today, the company announced the debut of c.ai Series - short-

arXiv:2607.07409v1 Announce Type: new Abstract: Speculative decoding accelerates LLM inference by drafting multiple tokens and verifying them in parallel. Block-parallel drafters such as DFlash furthe

arXiv:2607.07178v1 Announce Type: cross Abstract: Recent breakthroughs of Reinforcement Learning (RL) have highlighted its potential for complex agentic Large Language Model (LLM) tasks. However, exis

arXiv:2607.07702v1 Announce Type: new Abstract: The optimization of long-horizon agents increasingly relies on reflection-based mechanisms, where a large language model (LLM) acts as an optimizer to d

arXiv:2607.06839v1 Announce Type: cross Abstract: Existing NAS benchmarks (e.g., NAS-Bench, NATS-Bench) cover only narrow, task-specific regions of the architectural design space and lack cross-domain

arXiv:2607.07379v1 Announce Type: new Abstract: In agentic scientific machine learning (SciML), large language model (LLM) agents can discover surrogate models and select one by an automated score, ty

arXiv:2603.15245v2 Announce Type: replace Abstract: Empathy is central to human connection, yet people often struggle to express it effectively. In blinded evaluations, large language models (LLMs) ge

arXiv:2607.07052v1 Announce Type: cross Abstract: AI agents deployed for IT operations are typically permanent cost centers because every execution requires full LLM inference, even for previously sol

b9916 is a release of llama.cpp, an open-source C/C++ implementation for LLM inference . The release represents part of the project's rapid development cycle, with binaries available for multiple plat

b9923 is a release build of llama.cpp, an open-source C/C++ project for LLM inference with minimal setup and state-of-the-art performance on various hardware . The specific b9923 build includes binary

Release b9925 of llama.cpp is a version update for the LLM inference in C/C++ project. This build is part of the project's frequent release cycle, which can publish multiple releases in a single day ,

arXiv:2607.06140v1 Announce Type: new Abstract: Large language model (LLM) agents require post-training methods that can improve long-horizon decision making from environment feedback. However, existi

arXiv:2607.06447v1 Announce Type: new Abstract: Recent LLM-based mathematical reasoning agents have begun to tackle research-level problems and, in several cases, have contributed to the resolution of

arXiv:2607.06233v1 Announce Type: new Abstract: LLM-powered data agents are playing an increasingly important role in data-driven decision making. However, existing data agents struggle to generalize

In the agentic era, AI is evolving from answering questions to reasoning and taking action. Companies who want to lead in this next phase of AI need computing infrastructure that’s designed and optimi

arXiv:2607.05478v1 Announce Type: new Abstract: Loop invariant inference is a fundamental yet challenging problem in program verification. Recent LLM-aided guess-and-check techniques have shown strong

OpenWiki 0.0.3 just launched with tons of bug fixes and improvements! Some notable changes: - 'openai-compatible' provider to support any LLM provider that supports the OpenAI API spec! Thank you @bra

arXiv:2607.05915v1 Announce Type: new Abstract: PCB routing is the task of connecting the nets of a board with copper traces under strict design rules, yet learning-based methods still lag behind rule