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Paper Citation Record · LEDGER

Reward Design with Language Models

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 35 inbound Pith citation observations for arXiv:2303.00001.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2303.00001 v1

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measured 0 of 0 reference resolution

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measured 35 of 35 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 35 of 35 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T01:04:04.069804Z

measured 0 of 1 external citation measurements

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Source: arxiv_reference, observed 2026-07-03T04:47:38.286725Z

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Outbound references

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Pith citing papers

Observation d23a82d5-3c8d-410b-b9e7-3dd456ea4d2c · inbound

VoxPoser: Composable 3D Value Maps for Robotic Manipulation with Language Models cites this paper.

VoxPoser: Composable 3D Value Maps for Robotic Manipulation with Language Models Reward Design with Language Models

Reference 76

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arxiv_id, observed 2026-05-13T08:57:22.564735Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-13T08:57:22.299028Z digest=sha256:675a0198391f0050ce42fd9ea73a9057919a479258a911cb3a4c34a7fa8dfd2a

Observation 4837da17-58ba-4590-bce9-46fbd5cafc6c · inbound

Efficiently Generating Expressive Quadruped Behaviors via Language-Guided Preference Learning cites this paper.

Efficiently Generating Expressive Quadruped Behaviors via Language-Guided Preference Learning Reward Design with Language Models

Reference 5

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source=pdf_text observed=2026-08-09T01:04:04.069804Z digest=sha256:2dd2493c198e2d9053518afecd3a706c616bf39f2a9932859b77edd54294e56c

Observation eedeb1d1-d01b-488b-bf83-d900cfbef269 · inbound

Divide-Fuse-Conquer: Eliciting "Aha Moments" in Multi-Scenario Games cites this paper.

Divide-Fuse-Conquer: Eliciting "Aha Moments" in Multi-Scenario Games Reward Design with Language Models

Reference 12

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source=pdf_text observed=2026-08-07T15:07:04.302130Z digest=sha256:3da87b722d5853a41a56f07795b8476c50935b184cab4dd3e2540d61603e96cc

Observation 20383376-18c4-4a35-860a-eda6c56fc415 · inbound

Where You Go is Who You Are: Behavioral Theory-Guided LLMs for Inverse Reinforcement Learning cites this paper.

Where You Go is Who You Are: Behavioral Theory-Guided LLMs for Inverse Reinforcement Learning Reward Design with Language Models

Reference 22

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source=arxiv_source observed=2026-08-07T14:54:15.052114Z digest=sha256:0538cf9354bc4663b4e096f3214c042b5c3e809a10c92c27e6dd5f25075ea8ca

Observation e2c8dac2-a844-4e4f-a062-14f1f34ff23c · inbound

LLM-Guided Reinforcement Learning: Addressing Training Bottlenecks through Policy Modulation cites this paper.

LLM-Guided Reinforcement Learning: Addressing Training Bottlenecks through Policy Modulation Reward Design with Language Models

Reference 13

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source=pdf_text observed=2026-08-07T13:53:38.843038Z digest=sha256:66431305aadadba5317c458b9553dd0bf955134dc78691de8fff944bd7ca3c12

Observation 89208768-7722-478d-a081-5d8dfc6c7f02 · inbound

An evaluation of LLMs for generating movie reviews: GPT-4o, Gemini-2.0 and DeepSeek-V3 cites this paper.

An evaluation of LLMs for generating movie reviews: GPT-4o, Gemini-2.0 and DeepSeek-V3 Reward Design with Language Models

Reference 73

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source=pdf_text observed=2026-08-07T12:12:54.004545Z digest=sha256:f46d99c942b5a0b60da848466717166c86d4a5d7122fa0487d768b433df23da5

Observation cd972443-e59a-40ce-b06d-3303f40eea88 · inbound

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively cites this paper.

Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-Effectively Reward Design with Language Models

Reference 13

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source=arxiv_source observed=2026-08-07T12:11:43.508406Z digest=sha256:c05835a3956e87fbb2458dee03e507ce993f40fdea68709f62a82216bcd4daf9

Observation c49e6e44-5eb9-430d-b0db-fbe209d244c6 · inbound

Agentic Episodic Control cites this paper.

Agentic Episodic Control Reward Design with Language Models

Reference 43

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source=pdf_text observed=2026-08-07T11:50:00.420509Z digest=sha256:c7b30c69d93faf5cdb450a23d1b7c1549a6939366b8878ea4e8e0bce532fa749

Observation de54f59e-6712-4905-8a83-7fe6714d6b9d · inbound

Sign-SZPO: Provable Preference-based Reinforcement Learning with an Unknown Link Function cites this paper.

Sign-SZPO: Provable Preference-based Reinforcement Learning with an Unknown Link Function Reward Design with Language Models

Reference 10

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source=arxiv_source observed=2026-08-07T11:20:10.973403Z digest=sha256:5ea7559462d5da75f99d191a2346620c377468befdc5118ab83ac4607c593fb6

Observation 0e6cf36c-3d6b-4d3e-a5a5-6284597625a8 · inbound

ACTLLM: Action Consistency Tuned Large Language Model cites this paper.

ACTLLM: Action Consistency Tuned Large Language Model Reward Design with Language Models

Reference 38

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source=pdf_text observed=2026-08-06T22:34:08.994748Z digest=sha256:4de3b27947179c4b1befb8581af53cac4756876487fae01f4c2e30a502c3dfe2

Observation add81e89-0e28-4c1e-b6a8-8551fdc962c9 · inbound

Prompt Informed Reinforcement Learning for Visual Coverage Path Planning cites this paper.

Prompt Informed Reinforcement Learning for Visual Coverage Path Planning Reward Design with Language Models

Reference 16

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source=pdf_text observed=2026-08-06T17:39:45.103900Z digest=sha256:9414eee4808fa4aaff0588865ef90009afc621b36220cac5b1a6472ae2ce510e

Observation 1c00c216-2a6c-4e00-bfd4-e78c84b992a8 · inbound

FOUNDER: Grounding Foundation Models in World Models for Open-Ended Embodied Decision Making cites this paper.

FOUNDER: Grounding Foundation Models in World Models for Open-Ended Embodied Decision Making Reward Design with Language Models

Reference 22

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source=arxiv_source observed=2026-08-06T17:12:28.663704Z digest=sha256:c0c2c421c506aa4bfbe83e010049180817636b6d2e3b24f1124c49819eee6dda

Observation 33e0d3f5-5f7a-4d3d-a8d7-a3ec2544814f · inbound

Towards Reliable, Uncertainty-Aware Alignment cites this paper.

Towards Reliable, Uncertainty-Aware Alignment Reward Design with Language Models

Reference 21

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source=arxiv_source observed=2026-08-06T15:40:15.257918Z digest=sha256:62a1c8189e1702799c8f59cf5ef9d9440057acaaf7d51a1856f7044dfd82c107

Observation 158fe600-ef6b-423d-b6c2-3bc5a8a134f2 · inbound

Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN cites this paper.

Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN Reward Design with Language Models

Reference 25

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source=pdf_text observed=2026-08-06T12:30:39.980782Z digest=sha256:d0748b6141549ac521546aa6cc1fce0241ffb54e13b80c69736865b73e185f29

Observation f305a4a6-4972-4115-b611-ad80f1e9c0ef · inbound

GPLight+: A Genetic Programming Method for Learning Symmetric Traffic Signal Control Policy cites this paper.

GPLight+: A Genetic Programming Method for Learning Symmetric Traffic Signal Control Policy Reward Design with Language Models

Reference 9

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source=pdf_text observed=2026-08-05T17:36:53.242484Z digest=sha256:c94567b9d82af265c0a33483e0bc482efab643c9d34b53ef9babb382b05ecd23

Observation 68ebd632-382e-45fe-8ad4-a5484af427e8 · inbound

Toward Edge General Intelligence with Agentic AI and Agentification: Concepts, Technologies, and Future Directions cites this paper.

Toward Edge General Intelligence with Agentic AI and Agentification: Concepts, Technologies, and Future Directions Reward Design with Language Models

Reference 232

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source=pdf_text observed=2026-08-05T16:21:00.388060Z digest=sha256:b6ad00fb27bee1791c1e7e0f1ec6d444e793b4560162ab7c15dbc4138d851727

Observation 0d87d1aa-846d-47c2-8241-a9f836e426a5 · inbound

RoboInspector: Unveiling the Unreliability of Policy Code for LLM-enabled Robotic Manipulation cites this paper.

RoboInspector: Unveiling the Unreliability of Policy Code for LLM-enabled Robotic Manipulation Reward Design with Language Models

Reference 23

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source=pdf_text observed=2026-08-05T14:20:39.757357Z digest=sha256:81e6ce4ce1b7a9fd71bec5ca75ac940a490464fdb623b71e2d0a9a49f7c560f3

Observation 53f15e63-da33-4bec-97ac-afdc54c976d8 · inbound

Reward Evolution with Graph-of-Thoughts: A Bi-Level Language Model Framework for Reinforcement Learning cites this paper.

Reward Evolution with Graph-of-Thoughts: A Bi-Level Language Model Framework for Reinforcement Learning Reward Design with Language Models

Reference 28

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source=pdf_text observed=2026-08-04T16:06:58.488030Z digest=sha256:6fcc9b0c469406ca9a451c08e20358e528641e200cfebd36b348d7ab5504fe0f

Observation 8d415c79-628b-4620-92da-edc874336346 · inbound

LLM-Guided Task- and Affordance-Level Exploration in Reinforcement Learning cites this paper.

LLM-Guided Task- and Affordance-Level Exploration in Reinforcement Learning Reward Design with Language Models

Reference 22

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arxiv_id, observed 2026-05-18T15:21:32.889019Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-18T15:19:30.609974Z digest=sha256:fc894a1c90f1ba4c9761227536772029e79c298f2a4380d978b02eb70b19d171

Observation 0c805b36-670c-40b6-a7f6-f052dc25baf7 · inbound

Efficient Onboard Vision-Language Inference in UAV-Enabled Low-Altitude Economy Networks via LLM-Enhanced Optimization cites this paper.

Efficient Onboard Vision-Language Inference in UAV-Enabled Low-Altitude Economy Networks via LLM-Enhanced Optimization Reward Design with Language Models

Reference 33

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source=pdf_text observed=2026-08-04T10:37:26.093669Z digest=sha256:46228515d444d1639512cdc305c60d8fb509c38ee92987474c75120634d40faf

Observation 587ece49-1ab1-4654-ac28-0f2667bb4dd4 · inbound

InfiMed-ORBIT: Aligning LLMs on Open-Ended Complex Tasks via Rubric-Based Incremental Training cites this paper.

InfiMed-ORBIT: Aligning LLMs on Open-Ended Complex Tasks via Rubric-Based Incremental Training Reward Design with Language Models

Reference 17

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source=pdf_text observed=2026-08-04T09:22:42.928860Z digest=sha256:22c3810f9abac32bf87f2643941e071423778bc607fe81943341b0ad128da07e

Observation e7182a7d-daf9-4bc4-82b3-89d1677e696b · inbound

Debate2Create: Robot Co-design via Multi-Agent LLM Debate cites this paper.

Debate2Create: Robot Co-design via Multi-Agent LLM Debate Reward Design with Language Models

Reference 16

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source=pdf_text observed=2026-08-04T07:27:03.942685Z digest=sha256:66bfdc88af2af201e3032b8f7a858e81b9474de1c34f2c1ed56a11716ec5196c

Observation ebcf14d4-251c-4889-8f75-1e163c19b504 · inbound

What Is Preference Optimization Doing, and Why? cites this paper.

What Is Preference Optimization Doing, and Why? Reward Design with Language Models

Reference 38

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arxiv_id, observed 2026-05-21T18:40:28.991254Z

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source=pdf_text observed=2026-05-21T18:37:48.161545Z digest=sha256:fc46bf403c59a59303b977a563a8ae8f9caae5d1d28ddb1a7ed6232931c479bc

Observation dffd4cd3-bcf8-45cd-b02b-63d131037c6a · inbound

From Perception to Planning: Evolving Ego-Centric Task-Oriented Spatiotemporal Reasoning via Curriculum Learning cites this paper.

From Perception to Planning: Evolving Ego-Centric Task-Oriented Spatiotemporal Reasoning via Curriculum Learning Reward Design with Language Models

Reference 9

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arxiv_id, observed 2026-05-11T08:30:58.248439Z

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source=pdf_text observed=2026-05-10T16:35:36.083682Z digest=sha256:f7383a6c66e4b2b07dfeaa863b81cb9ad880f01bff58e5f2978cae02f61fba1a

Observation e2cb6821-a8dc-49f6-adeb-643f1b2a32b6 · inbound

PERSA: Reinforcement Learning for Professor-Style Personalized Feedback with LLMs cites this paper.

PERSA: Reinforcement Learning for Professor-Style Personalized Feedback with LLMs Reward Design with Language Models

Reference 40

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arxiv_id, observed 2026-05-11T15:51:42.642392Z

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source=arxiv_source observed=2026-05-09T19:09:07.557773Z digest=sha256:fcba8193bba21563ddef208be622894c7d1ba15782bf28b16dd92f34430bbee5

Observation 95fafb7d-3014-4d2b-b6dc-572abe964758 · inbound

Enhanced LLM Reasoning by Optimizing Reward Functions with Search-Driven Reinforcement Learning cites this paper.

Enhanced LLM Reasoning by Optimizing Reward Functions with Search-Driven Reinforcement Learning Reward Design with Language Models

Reference 16

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arxiv_id, observed 2026-05-09T06:00:35.202959Z

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source=pdf_text observed=2026-05-08T19:14:22.162163Z digest=sha256:23b70f7c0ebc6cf0c54397dd81e1ce995d61eeb655af44b50df0a925d25bdcdb

Observation dfbba3b9-0fd3-4fa0-86ff-dd484a6ff85b · inbound

Enhanced LLM Reasoning by Optimizing Reward Functions with Search-Driven Reinforcement Learning cites this paper.

Enhanced LLM Reasoning by Optimizing Reward Functions with Search-Driven Reinforcement Learning Reward Design with Language Models

Reference 16

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arxiv_id, observed 2026-05-11T03:50:58.007955Z

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source=pdf_text observed=2026-05-11T02:10:46.725354Z digest=sha256:42a641990df3901abf52313553907c8898cf95ca7fe93b5a0180749f25bacfa2

Observation a11363b3-61f5-44ea-97ff-02d463e3429f · inbound

Reflective Prompted Policy Optimization: Trajectory-Grounded Revision and Salience Bias cites this paper.

Reflective Prompted Policy Optimization: Trajectory-Grounded Revision and Salience Bias Reward Design with Language Models

Reference 6

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arxiv_id, observed 2026-05-12T08:41:24.007336Z

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source=pdf_text observed=2026-05-12T00:51:58.315109Z digest=sha256:b1ea99629f26bcdf85a092f98a29983a99391a0cf6b6050dd27c28a611050983

Observation 5ee0afc7-d13a-45fd-8fc6-79051e300cb8 · inbound

EvoNav: Evolutionary Reward Function Design for Robot Navigation with Large Language Models cites this paper.

EvoNav: Evolutionary Reward Function Design for Robot Navigation with Large Language Models Reward Design with Language Models

Reference 18

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arxiv_id, observed 2026-05-13T05:27:18.924884Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-13T05:19:38.587352Z digest=sha256:610cac471ec5bcc1205dfd377b55c08de490d09acb7b931516d7b13fae38cbf7

Observation 1a53cd80-346a-4d58-93e6-720fad5239bf · inbound

DuIVRS-2: An LLM-based Interactive Voice Response System for Large-scale POI Attribute Acquisition cites this paper.

DuIVRS-2: An LLM-based Interactive Voice Response System for Large-scale POI Attribute Acquisition Reward Design with Language Models

Reference 26

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arxiv_id, observed 2026-05-20T10:33:12.905500Z

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source=arxiv_source observed=2026-05-20T10:30:48.957568Z digest=sha256:6e4783d9321f7c65beb5fe1c343f4dda81c99908c2db2ef457bfd4d1a1a93bb1

Observation 19b9b349-5bd5-431a-80e2-fc59e6710367 · inbound

Uncertainty-Aware LLM-Guided Policy Shaping for Sparse-Reward Reinforcement Learning cites this paper.

Uncertainty-Aware LLM-Guided Policy Shaping for Sparse-Reward Reinforcement Learning Reward Design with Language Models

Reference 11

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arxiv_id, observed 2026-07-02T11:56:55.227147Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-28T02:47:16.737433Z digest=sha256:21d51bd7b79d126da402c8d8fc9a0f680243e012d3e5566725dfe8e22da8caa5

Observation c880b2a2-7d08-4386-8ba3-647b6b3461c4 · inbound

Representation-Aware Advantage Estimation: Your Reward Model Provides More Than A Scalar Output cites this paper.

Representation-Aware Advantage Estimation: Your Reward Model Provides More Than A Scalar Output Reward Design with Language Models

Reference 33

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arxiv_id, observed 2026-07-03T04:47:38.288260Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-27T13:39:17.701196Z digest=sha256:2a5c4b1fab7d7923274f614225596e2a480a3b93583aeb2ee51f689cf7b09557

Observation e6ae1a8e-4136-4dfc-aa6e-dccf1d2d497b · inbound

ARKD: Adaptive Reinforcement Learning-Guided Bidirectional KL Divergence Distillation for Text Generation cites this paper.

ARKD: Adaptive Reinforcement Learning-Guided Bidirectional KL Divergence Distillation for Text Generation Reward Design with Language Models

Reference 46

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arxiv_id, observed 2026-06-30T06:04:21.642435Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-30T05:59:13.483829Z digest=sha256:f9ebb23058879cbbf8510de17a0b4eab9f75ad23837e51a31a5e8255db462810

Observation 29c5a56c-d257-4a05-9423-3de842757ff7 · inbound

TAPAS: Throughput-adaptive Perception for Autonomous Systems cites this paper.

TAPAS: Throughput-adaptive Perception for Autonomous Systems Reward Design with Language Models

Reference 25

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source=pdf_text observed=2026-08-01T18:24:05.608019Z digest=sha256:da5aada8ddf406066209df48f2dba85dccf76dcc48e12f54af6c4b4eb0e06416

Observation 913bc2cf-6378-4779-8888-177241f91b5a · inbound

Computational models of pragmatic reasoning with flexible generation of meaning and expression alternatives cites this paper.

Computational models of pragmatic reasoning with flexible generation of meaning and expression alternatives Reward Design with Language Models

Reference 150

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source=arxiv_source observed=2026-08-01T15:27:06.396909Z digest=sha256:02754988a6c5a179b03bf89513b5f619eefbb99e37a5af02b4fdeda42ee8071c