pith. sign in

hub Canonical reference

Agent-RewardBench: Towards a unified benchmark for reward modeling across perception, planning, and safety in real- world multimodal agents

Canonical reference. 90% of citing Pith papers cite this work as background.

19 Pith papers citing it
Background 90% of classified citations

hub tools

citation-role summary

background 9 dataset 1

citation-polarity summary

years

2026 17 2025 2

polarities

background 9 support 1

representative citing papers

Code Generation by Differential Test Time Scaling

cs.SE · 2026-05-19 · unverdicted · novelty 7.0

DiffCodeGen clusters code candidates by behavioral similarity from fuzzing-synthesized inputs and selects the largest cluster's medoid, matching or exceeding prior test-time scaling methods with far less token and time cost.

Evaluation of Agents under Simulated AI Marketplace Dynamics

cs.IR · 2026-04-15 · unverdicted · novelty 6.0

Marketplace Evaluation uses repeated-interaction simulations to assess information access systems with marketplace-level metrics such as retention and market share that complement traditional accuracy measures.

ReflectCAP: Detailed Image Captioning with Reflective Memory

cs.AI · 2026-04-14 · unverdicted · novelty 6.0

ReflectCAP distills model-specific hallucination and oversight patterns into Structured Reflection Notes that steer LVLMs toward more factual and complete image captions, reaching the Pareto frontier on factuality-coverage trade-offs.

Reinforcement Learning from Human Feedback

cs.LG · 2025-04-16 · unverdicted · novelty 2.0

The book introduces the origins, mathematical setup, and optimization stages of RLHF including reward modeling, reinforcement learning, rejection sampling, and direct alignment algorithms.

citing papers explorer

Showing 19 of 19 citing papers.