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Pulse · forbes.com

forbes.com · Oct 30

Token Resistance: Overcoming Fear And Doubt In The AI Agent Era

Agentic transformation in the business has implications far beyond simply employing agents as personal assistants.

Pulse · finance.yahoo.com

finance.yahoo.com · Oct 30

Broadcom Stock Outlook Hinges On AI Chip Growth And Anthropic Partnership

Broadcom Inc. recently reported sharp growth in AI semiconductor revenue, expanded custom accelerator work with Anthropic and Meta, and shipped 89 security fixes in TrueSource Spring Enterprise while rolling out new application security and patch automation capabilities.

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Top picks this weekarXiv

arXiv

Oct 29

Elucidating the Design Space of LM Data Attribution

Data attribution methods for Language Models (LMs) are typically evaluated using downstream tasks like fact retrieval. However, existing evaluations vary multiple dataset properties simultaneously, making it impossible to isolate exactly why an attribution algorithm fails. To diagnose these failures, we explore the design space of LLM data attribution, with a primary focus on evaluation. We introduce the Controlled Attribution Benchmark (CATT) for fact tracing, in which we fine-tune LLMs on entirely fictitious knowledge, providing unambiguous ground truth for attribution. This synthetic setup allows us to systematically alter one dataset configuration at a time, such as document redundancy and lexical distractors. With this configurable evaluation, we demonstrate that redundancy and distractors consistently degrade attribution performance. Rather than proposing a new estimator, we examine two design choices that are underexplored: the loss used to compute gradients and how per-token attribution scores are aggregated into a document score. We find that the true causal evidence within a training document is highly localized, but standard methods dilute this evidence into noise by…

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arXiv

Sep 18

SkillIR: Evolving Scene-Aware Skills for Agentic Image Restoration

This paper studies agentic image restoration, in which multimodal agents coordinate specialized restoration tools to recover images affected by complex degradations. Existing restoration agents often derive complete tool-use plans from the original degraded image or retrieve…

arXiv

Sep 18

OmniVChat: Synthesizing, Benchmarking, and Training for Native Audio-Visual Dialogue

We define OmniVChat (Omni Video Chat) as the task of native audio-visual dialogue between a user and an omni model. In OmniVChat, omni models directly and simultaneously receive audio and video from a user and return text. The user's query is embedded in the audio and video,…

arXiv

Sep 18

PSEE: Progressive Sensor Event Expansion for Point-Supervised Temporal Action Localization

Temporal action localization (TAL) in wearable sensor streams identifies action classes and temporal boundaries, enabling finer-grained activity understanding than conventional action recognition. However, training typically requires costly start--end annotations for every…

arXiv

Sep 18

AtomEgo: Exploring Ego-Robot Integration for Embodied Foundation Model Pretraining

Embodied foundation models are constrained by the limited scale and diversity of robot demonstrations, motivating the use of large-scale egocentric human interaction data. However, how to effectively incorporate such data into embodied-model pre-training remains unclear because…

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